Tuesday, October 31, 2017

RavenDB 4.0 Unsung Heroes: Automatic Conflict Resolution

DZone Database Zone
RavenDB 4.0 Unsung Heroes: Automatic Conflict Resolution
RavenDB 4.0 Unsung Heroes: Automatic Conflict Resolution

RavenDB is a distributed database, and it has been a distributed database since pretty much the very start — although over time, we have been making the distribution part easier and easier. You might be able to tell that the design of RavenDB was heavily influenced by the Dynamo paper and RavenDB implements a multi-master system that allows every node to accept writes and disseminate them across the network.

This is great because it ensures that we have a high stability in the face of error, but this also opens us up to some interesting failure modes. In particular, if a document is modified in two nodes at the same time, there is no way to immediately detect that — unlike in a single master system, where such a thing would be detected but requires at least a majority of the nodes to be up. A scenario where we have concurrent modifications on the same document on a different server is called a conflict and is something that RavenDB is quite able to detect and handle.

AWS re:Invent 2017 - Pub Crawl Expands!

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#Data -AWS re:Invent 2017 - Pub Crawl Expands!

Bringing Continuous Delivery to the Database

DZone Database Zone
Bringing Continuous Delivery to the Database
Bringing Continuous Delivery to the Database

This article is featured in the new DZone Guide to Databases. Get your free copy for more insightful articles, industry statistics, and more!

Databases are often seen as the poor relative in software development. The clunky bits at the backend that store the data while the front-end applications do their magic. The grey boxes that are updated at the conclusion of the software development process and often cause problems.

Calculating the ROI of Log Analysis Tools

DZone Database Zone
Calculating the ROI of Log Analysis Tools
Calculating the ROI of Log Analysis Tools

Anyone in a technology organization can relate to a certain frustration: You know that adopting a certain tool or practice would help you. So you charge forward with the initiative, looking for approval. But then someone — a superior, most likely — asks you to justify it. "Give me the business case for it," they say. And then, flummoxed a little, the gears start turning in your head. Today, I'd like to talk about that very issue in the specific context of log analysis tools.

If you have significant operations of any kind in production, you're almost certainly generating logs. If not, you should be. You're also probably monitoring those logs, in some fashion or another. And if you're consuming them, you're analyzing them in some fashion or another. But maybe you're doing this manually, and you'd rather use a tool for log analysis. How do you justify adopting that tool? How do you justify paying for it?

Table Syntax in SQL Server 2017

DZone Database Zone
Table Syntax in SQL Server 2017
Table Syntax in SQL Server 2017

Data or information for a database is stored in tables. Tables are uniquely identified by their names and are comprised of columns and rows. A table has a specified number of columns but can have any number of rows. Columns contain the column name and data type for the column. Rows contain the records or data for the columns.

Let's look at the syntax for different MS SQL commands, as well as an example of how exactly each command works.

Monday, October 30, 2017

Efficient Container Orchestration for the Enterprise

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#Data -Efficient Container Orchestration for the Enterprise

Going Beyond Data Management

DZone Database Zone
Going Beyond Data Management
Going Beyond Data Management

Well-managed data is the need of every business to maintain the efficiency. It is a crucial process and requires an efficient team to record the data accurately.

However, if you are an owner of a small- to mid-sized business, it will not be easy for you to manage your data alone. Trying to do this will eventually disrupt your other tasks. In order to establish yourself in the market and keep pace with your rivals, structured and well-organized data is essential for your business, as it helps you have readily available data whenever you need it.

GorillaStack: Secure Automation Tools as a Service

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#Data -GorillaStack: Secure Automation Tools as a Service

AWS Knowledge Center Videos: How do I upgrade a PV driver?

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#Data -AWS Knowledge Center Videos: How do I upgrade a PV driver?

Database Deep Dive: The NoSQL Edition

DZone Database Zone
Database Deep Dive: The NoSQL Edition
Database Deep Dive: The NoSQL Edition

Welcome back! In our last Database deep dive, we talked about SQL and all the things you need to know about it, such as custom date formatting in SQL Server and jobs for the SQL expert. This time around, we're going to be learning about SQL's sibling: NoSQL. Read on to check out some of the top NoSQL articles on DZone to get you acquainted with the topic, check out some jobs that might be of interest to you if you're a NoSQL expert, and more!   

K(No)w (No)SQL

Check out some of the top NoSQL-related articles on DZone. These articles are best read in order, so follow along and enhance your NoSQL knowledge!

Be Kind to Your Log File (and Those Reading It)

DZone Database Zone
Be Kind to Your Log File (and Those Reading It)
Be Kind to Your Log File (and Those Reading It)

The log file has existed since programmer time immemorial. The software world moves really fast, but it's not hard to imagine someone decades ago poring over a log file. This is, perhaps, as iconic as programming itself.

But sadly, for many shops, the approach hasn't really evolved in all of that time. "Dump everything to a file and sort it out later, if you ever need it," was the original idea. And that holds up to this day.

InfluxDB vs. Elasticsearch for Time Series Analysis

DZone Database Zone
InfluxDB vs. Elasticsearch for Time Series Analysis
InfluxDB vs. Elasticsearch for Time Series Analysis

Choosing which storage solution to use for time series data is not a straightforward task, to say the least. Today, one is almost spoilt for choice as there are some great alternatives out there, but this article attempts to shed some light on two of these solutions: Elasticsearch and InfluxDB.

Why this comparison? While InfluxDB was designed for time series data, Elasticsearch was designed for (and is mostly used for) document indexing. However, despite this design and functional disparity, Elasticsearch is used by many for time series data and we wanted to check how well these two databases perform.

Sunday, October 29, 2017

Tracking Real-Time Weather Updates With InfluxDB

DZone Database Zone
Tracking Real-Time Weather Updates With InfluxDB
Tracking Real-Time Weather Updates With InfluxDB

Not long ago, I started wondering if I could use InfluxDB to track weather events in real-time. We've had more than a few significant weather events recently — notably named Harvey, Irma, and Maria — and I wanted to see if I could do some tracking, and possibly alerting, of new tropical storm and hurricane events. It turns out that the National Hurricane Center provides live RSS/XML feeds of all the Atlantic Basin Tropical Cyclones (they have feeds of other areas, as well). Perfect! Just what I'm looking for. I'll walk you through how I set up the RSS Feed Reader, parsed the XML feed, and inserted the data into my InfluxDB instance. I'll also show some of the dashboards I created to track these storms. I even decided to see if I could set up some Grafana dashboards, so I'll show you how to do that, as well.

Getting the XML RSS Feed

The RSS feeds are all listed on the National Hurricane Center's page, so finding it was easy. Parsing it was a bit more challenging. I chose to use Node-Red again since it has some easy-to-use built-in data sources, one of which is an RSS Feed Reader. Here's the entirety of my Node-Red flow:

Saturday, October 28, 2017

5 Questions With the Head of Tarantool, Dennis Anikin

DZone Database Zone
5 Questions With the Head of Tarantool, Dennis Anikin
5 Questions With the Head of Tarantool, Dennis Anikin

Tarantool is one of the newest, most sophisticated players to the DBMS game in North America. In a few short months, Tarantool has become a highly sought-after technology due to its powerful stored procedures, SQL support, smart cache, and the speed of one million ACID transactions on a single CPU core. I had the opportunity to chat with Tarantool’s General Manager, Dennis Anikin, to learn more about the history of Tarantool, how it works, and what the future plans are for the expanding company.

Tell us a bit about yourself and your background. How did you get into the DBMS space?

Friday, October 27, 2017

Guard Against Fraud and Financial Crime with NICE Actimize & AWS

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#Data -Guard Against Fraud and Financial Crime with NICE Actimize & AWS

VMware Cloud on AWS

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#Data -VMware Cloud on AWS

Aggregate and Index Data into Elasticsearch Using Logstash and JDBC

DZone Database Zone
Aggregate and Index Data into Elasticsearch Using Logstash and JDBC
Aggregate and Index Data into Elasticsearch Using Logstash and JDBC

In my previous posts (here and here), I showed you how to index data into Elasticsearch from a SQL DB using JDBC and Elasticsearch JDBC importer library. In the first article, I mentioned some of the shortcomings of using the importer library, which I have copied here:

No support for ES version 5 and above. There is a possibility of duplicate objects in the array of nested objects, but de-duplication can be handled at the application layer. There can be a possibility of delay in support for latest ES versions.

All the above shortcomings can be overcome by using Logstash and its following plugins:

NuoDB: Index Management and Performance Improvements

DZone Database Zone
NuoDB: Index Management and Performance Improvements
NuoDB: Index Management and Performance Improvements

Everyone likes to save time, right? After all, it even feels good to gain time back. You can do something more important or fun with that new-found time or just get to the next part of your day a bit sooner. We like our little time savers — like pre-ground coffee, automatic garage door openers, or even that magic button on your refrigerator that, when pressed, deposits ice in your drink!

Well at NuoDB, we realize the DBA has a number of tasks that periodically need to be performed throughout the day, week or month, and that some of those tasks can be automated to gain back valuable time. In fact, NuoDB has always had maintenance-free indexes. This saves our customers time by not requiring DBAs to schedule a special time to run index rebuilds to rebalance and reorganize indexes. Yep, that's right: NuoDB automatically rebuilds indexes as needed in the background, making indexes rebuilds a thing of the past.

Recap: Brad Anderson at JAMF Nation User Conference 2017

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#Data -Recap: Brad Anderson at JAMF Nation User Conference 2017

Introduction to AWS EdStart – EdTech Startups on AWS

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#Data -Introduction to AWS EdStart – EdTech Startups on AWS

Top Metrics to Monitor in Your MySQL Databases (Part 1)

DZone Database Zone
Top Metrics to Monitor in Your MySQL Databases (Part 1)
Top Metrics to Monitor in Your MySQL Databases (Part 1)

As tables increase in size and more and more users come online, it becomes increasingly necessary to fine-tune your database server from time to time. The secret to knowing what adjustments need to be made is to perform regular monitoring. Most databases offer dozens — if not hundreds — of performance metrics that you can assess.

In an earlier blog, we showed a number of ways to determine the cause(s) of MySQL database performance issues using a couple of built-in tools. With this two-part series, we will focus on monitoring key performance metrics. In part one, we’ll:

Thursday, October 26, 2017

Power BI Bookmarks, Selections and Toggles

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#Data -Power BI Bookmarks, Selections and Toggles

Introduction to AWS EdStart – EdTech Startups on AWS

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#Data -Introduction to AWS EdStart – EdTech Startups on AWS

Recap: Brad Anderson at JAMF Nation User Conference 2017

Data Videos
#Data -Recap: Brad Anderson at JAMF Nation User Conference 2017

Counting Nodes With Multiple Labels

DZone Database Zone
Counting Nodes With Multiple Labels
Counting Nodes With Multiple Labels

We have over 6,000 users in our #neo4j-users slack channel and get all kinds of requests. About a month ago Thomas Shields asked:

Should counting the set of things with 2 labels really take so long? I've got 48M nodes with LabelA and LabelB and the query MATCH (n:LabelA:LabelB) RETURN COUNT(n) is taking 80-90 seconds.

Let's see what's going on by creating a small version of his graph. We will create 1M nodes of LabelA, then 1M nodes with both LabelA and LabelB, and then 1M nodes with just Label B:

How Advanced Is Database DevOps in Financial Services?

DZone Database Zone
How Advanced Is Database DevOps in Financial Services?
How Advanced Is Database DevOps in Financial Services?

Whether you're exploring the advantages of DevOps or are already fully immersed in the journey, including the database brings additional advantages. But how are you performing compared to the competition? What could you do better? What's the benchmark you should be aiming for?

To help companies answer these questions, Redgate has created a Database DevOps Maturity Assessment tool, which evaluates where you are now, shows how you compare with your peers, and makes recommendations for how to move forward.

5 Hidden Database Deployment Costs

DZone Database Zone
5 Hidden Database Deployment Costs
5 Hidden Database Deployment Costs

Today, database deployments that change schema and logic are often performed via a manual, lengthy, and costly process. It is important to remember that a task that is expensive does not just cost the amount of money paid in resources and time. There are unintended economic and opportunity costs that are hidden and ignored.

Here are the five hidden costs associated with today’s approach to deploying database changes.

How to Install a Monitoring Dashboard in Under 5 Minutes Using InfluxData

DZone Database Zone
How to Install a Monitoring Dashboard in Under 5 Minutes Using InfluxData
How to Install a Monitoring Dashboard in Under 5 Minutes Using InfluxData

I have my trusty MacBook Pro on which I do just about everything, so that’s what I’m going to install this dashboard on. Here’s what I’m working with:

I installed and configured InfluxDB, Chronograf, Telegraf, and Kapacitor and set up a quick system monitoring dashboard to keep track of some system stats — all in under five minutes.

Wednesday, October 25, 2017

Robocar Rally 2017 | Connecting Your Autonomous Vehicle

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#Data -Robocar Rally 2017 | Connecting Your Autonomous Vehicle

Real time threat protection with Microsoft Intelligent Security Graph

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#Data -Real time threat protection with Microsoft Intelligent Security Graph

REA: Multi-Region Deploys without Disruption

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#Data -REA: Multi-Region Deploys without Disruption

AWS Summit Series 2017: London - Deep Dive on Amazon Elastic File System (Amazon EFS)

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#Data -AWS Summit Series 2017: London - Deep Dive on Amazon Elastic File System (Amazon EFS)

How Symantec Cloud Workload Protection Secures LifeLock on AWS

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#Data -How Symantec Cloud Workload Protection Secures LifeLock on AWS

Working With Dates Using the Node.js Driver

DZone Database Zone
Working With Dates Using the Node.js Driver
Working With Dates Using the Node.js Driver

Node.js is an excellent platform for creating RESTful APIs that store and retrieve data using Oracle Database. node-oracledb is the driver maintained by Oracle that allows Node.js developers to connect to and utilize the database. As data crosses the boundaries between JavaScript and Oracle Database, the driver automatically converts it to native data types on either end. This post explores how that conversion process works for datetime values.

SQL execution and bind variables are the most common methods of moving data between Node.js and Oracle Database. When it comes to datetime values, the behavior of node-oracledb is the same regardless of the method used. The section in the documentation on result type mapping describes that behavior:

MySQL Point-in-Time Recovery: The Right Way

DZone Database Zone
MySQL Point-in-Time Recovery: The Right Way
MySQL Point-in-Time Recovery: The Right Way

In this blog, I'll look at how to do MySQL point-in-time recovery (PITR) correctly.

Sometimes, we need to restore from a backup and then replay the transactions that happened after the backup was taken. This is a common procedure in most disaster recovery plans where, for example, you accidentally drop a table/database or run an update/delete without the where clause and lose data.

How to Perform Database Testing Using Katalon Studio

DZone Database Zone
How to Perform Database Testing Using Katalon Studio
How to Perform Database Testing Using Katalon Studio

Katalon Studio allows users to create custom keywords to address specific needs. With custom keywords, you can connect to databases and perform database testing. This tutorial describes details on how to create custom keywords for database testing in Katalon Studio.

Below is a code sample demonstrating how to:

Tuesday, October 24, 2017

Siemens: Product Intelligence Automates Insights from Product Performance Data

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#Data -Siemens: Product Intelligence Automates Insights from Product Performance Data

Separate Keyspaces With Spring Data Cassandra

DZone Database Zone
Separate Keyspaces With Spring Data Cassandra
Separate Keyspaces With Spring Data Cassandra

Following on from my previous post, we will look into using multiple keyspaces within an application. This will be a relatively short post due to most of the content being covered in the earlier post, allowing us to focus on the code needed to allow multiple keyspaces and reasons why you might want to switch from using a single one to using multiple.

As mentioned a minute ago, Getting Started With Spring Data Cassandra contains fundamental information required in this post, including dependencies and code snippets that are not shown here.

Amazon RDS Performance Insights for Amazon Aurora

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TTS Discusses the Value of AWS Training and Certification

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#Data -TTS Discusses the Value of AWS Training and Certification

How Neo4j Is Making Graph Technology More Accessible

DZone Database Zone
How Neo4j Is Making Graph Technology More Accessible
How Neo4j Is Making Graph Technology More Accessible

Thanks to Jeff Morris, Head of Product Marketing at Neo4j, for taking me through two new additions that are making graph technology more accessible for developers, big data IT, and data scientists. The graph database ecosystem is evolving quickly as business owners express an interest in better data presentations.

The new contribution to the Hadoop ecosystem enables graph analytic capabilities for Spark, making Cypher available to the popular in-memory analytic engine.

Relational to JSON With Node.js

DZone Database Zone
Relational to JSON With Node.js
Relational to JSON With Node.js

Check out the other parts of this series here:

Relational to JSON in Oracle Database

Tracking Large Numbers From Databases in the Application Layer

DZone Database Zone
Tracking Large Numbers From Databases in the Application Layer
Tracking Large Numbers From Databases in the Application Layer

Today's conventional relational database management systems — such as Oracle, MS SQL, MySQL, etc. — are still relied on by many large-scale corporations. And being a large-scale company brings gigabyte-sized data that might have 150+ columns tables with it (apparently, you can have 1k columns on an Oracle DB table).

Naturally, a relational DB table having unique key columns is inevitable. This may include sequence objects in Oracle and MS SQL, serial objects in PostgreSQL, etc. Those columns are crucial to creating relations between tables and accessing the desired data.

Monday, October 23, 2017

What's New with AWS - Week of Oct 16, 2017

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#Data -What's New with AWS - Week of Oct 16, 2017

How TrueCar Gains Actionable Insights with Splunk Cloud

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#Data -How TrueCar Gains Actionable Insights with Splunk Cloud

Introduction to Liquibase and Managing Your Database Source Code

DZone Database Zone
Introduction to Liquibase and Managing Your Database Source Code
Introduction to Liquibase and Managing Your Database Source Code

In previous posts, I showed how you can manage SQL scripts lifecycle with the help of Oracle Developer Cloud Service (DevCS) as part of an overall Oracle DB DevOps solution. I wanted to add one more utility that might act as an alternative or addition to the SQL script managing: Liquibase.

Liquibase is an open-source solution for managing revisions of your database schema scripts. It works across various types of databases and supports various file formats for defining the DB structure. The feature that is probably most attractive in Liquibase is its ability to roll changes back and forward from a specific point — saving you from needing to know what was the last change/script you ran on a specific DB instance.

Working With Dates in JavaScript, JSON, and Oracle Database

DZone Database Zone
Working With Dates in JavaScript, JSON, and Oracle Database
Working With Dates in JavaScript, JSON, and Oracle Database

When I wrote a series of posts on creating JSON from relational data, I mentioned that dates could be tricky. That was a bit of an understatement. Dates and the time zone conversions that often go along with them can be outright daunting!

In this series, I hope to shed some light on the subject of dates in the context of JavaScript, JSON, and Oracle Database. As in the previous series, I'll base things on a RESTful API scenario. The focus here will be on tracking a date from the browser to the database and then back from the database to the browser.

The Tractor Beam of the Database in an API World

DZone Database Zone
The Tractor Beam of the Database in an API World
The Tractor Beam of the Database in an API World

I’m an old database person. I’ve been working with databases since my first job in 1987. Cobol. FoxPro. SQL Server. MySQL. I have had a production database in my charge accessible via the web since 1998. I understand how databases are the center of gravity when it comes to data — it's something that hasn’t changed in an API-driven world. This is something that will make microservices in a containerized landscape much harder than some developers will want to admit. The tractor beam of the database will not give up control to data so easily — either because of technical limitations, business constraints, or political gravity.

Databases are all about storage and access to data. And APIs are about access to data. They're about storage, and the control that surrounds it is what creates the tractor beam. Most of the reasons for control over the storage of data are not looking to do harm. Security. Privacy. Value. Quality. Availability. There are many reasons stewards of data want to control who can access data, and what they can do with it. However, once control over data is established, I find it often morphs and evolves in many ways, that it can eventually become harmful to meaningful and beneficial access to data — which is usually the goal behind doing APIs, but is often seen as a threat to the mission of data stewards, and results in a tractor beam that API-related projects will find themselves caught up in and find difficult to ever break free of.

AWS Knowledge Center Videos: How do I change the encryption key used by my RDS instance?

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#Data -AWS Knowledge Center Videos: How do I change the encryption key used by my RDS instance?

Why You Need an In-Memory Database for Your IIoT Project

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Why You Need an In-Memory Database for Your IIoT Project
Why You Need an In-Memory Database for Your IIoT Project

Databases for the Industrial Internet of Things need to accommodate fast-changing and often unstructured data sets, and must be capable of extensive horizontal scaling—as implementations can grow from hundreds to millions of sensors.

It is ideal to do as much processing as possible close to the data collection points themselves, i.e. the edge, because latency is introduced when data travels to remote servers. And this processing may require real-time analytics, allowing the application of strategies such as machine learning that facilitate near real-time business decisions.

What Developers Need to Know About Databases

DZone Database Zone
What Developers Need to Know About Databases
What Developers Need to Know About Databases

To gather insights on the state of databases today and their future, we spoke to 27 executives at 23 companies who are involved in the creation and maintenance of databases.

We asked these executives, "What skills do developers need to be proficient with databases?" Here's what they told us:

Sunday, October 22, 2017

Optimize N1QL Performance Using Request Profiling

DZone Database Zone
Optimize N1QL Performance Using Request Profiling
Optimize N1QL Performance Using Request Profiling

Couchbase Server 4.5 introduced a mechanism to keep an eye on executing requests so that slow performers can be highlighted.

This DZone article covers the subject of N1QL monitoring in great detail, but the question now is: We have the rioters; how do we check their demands?

Relational to JSON With ORDS

DZone Database Zone
Relational to JSON With ORDS
Relational to JSON With ORDS

Oracle REST Data Services (ORDS) was first released back in 2010 as the APEX Listener. REST support for JSON actually wasn't added until version 1.1 in 2011. Then in 2014, the product was renamed to Oracle REST Data Services to emphasize the commitment to REST.

At this point, ORDS does a lot! It still the best option for an APEX listener and APEX developers can still use the APEX GUI to create RESTful web services with ORDS. But there are new ways to create service definitions, including a GUI in SQL Developer and a PL/SQL API. We'll take a look at all three of those options in this post. We will not, however, be exploring the auto-REST enabling of schema objects or Simple Oracle Document Access (SODA) for REST capabilities. Those are exciting features I'll cover in future posts!

Saturday, October 21, 2017

Data Virtualization: A Secret Weapon for Businesses

DZone Database Zone
Data Virtualization: A Secret Weapon for Businesses
Data Virtualization: A Secret Weapon for Businesses

Data is growing every day. It is no longer all neatly delivered from relational tables, but can originate from a nearly unlimited number of sources, both structured and unstructured, including sensors, email, social media, and RESTful APIs.

That is why data virtualization is so useful—it brings clarity and simplicity to the data scattered across silos and the globe, so you can solve business problems.

Friday, October 20, 2017

Discover, Classify, and Protect Sensitive Data with Amazon Macie

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#Data -Discover, Classify, and Protect Sensitive Data with Amazon Macie

AWS Summit Milano 2017 | Marco Argenti Keynote [Italian]

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#Data -AWS Summit Milano 2017 | Marco Argenti Keynote [Italian]

When Should I Enable MongoDB Sharding?

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When Should I Enable MongoDB Sharding?
When Should I Enable MongoDB Sharding?

In this blog post, we will talk about MongoDB sharding and walk through the main reasons why you should start a cluster (independent of the approach you have chosen).

(Note: I covered this subject in my webinar How To Scale With MongoDB on Wednesday, October 18, 2017!)

How to Choose the MySQL innodb_log_file_size

DZone Database Zone
How to Choose the MySQL innodb_log_file_size
How to Choose the MySQL innodb_log_file_size

In this blog post, I’ll provide some guidance on how to choose the MySQL innodb_log_file_size.

Like many database management systems, MySQL uses logs to achieve data durability (when using the default InnoDB storage engine). This ensures that when a transaction is committed, data is not lost in the event of crash or power loss.

Relational to JSON With APEX_JSON

DZone Database Zone
Relational to JSON With APEX_JSON
Relational to JSON With APEX_JSON

APEX_JSON is a PL/SQL API included with Oracle Application Express (APEX) 5.0 that provides utilities for parsing and generating JSON. While APEX_JSON was primarily intended to be used by APEX developers, there are some hooks that can allow it to be used as a standalone PL/SQL package.

Solution

The following solution uses APEX_JSON to create the JSON that represents a department in the HR schema. APEX_JSON basically writes JSON content to a buffer. By default, the buffer used is the HTP buffer in the database, as that's what APEX reads. But as you can see with line 27, it's possible to redirect the output to a CLOB buffer instead. Once we've redirected the output, we can make API calls to open/close objects and arrays and write values to them. When we're done writing out the JSON we can make a call to get_clob_output to get the JSON contents. I've highlighted some of the relevant lines...

Thursday, October 19, 2017

Automate the Provisioning of Secure Developer Environments on AWS

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#Data -Automate the Provisioning of Secure Developer Environments on AWS

How Western Union Implemented Security Measures at Scale on AWS with Dome9

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#Data -How Western Union Implemented Security Measures at Scale on AWS with Dome9

Becoming an AWS Policy Ninja using AWS IAM and AWS Organizations [SEC302]

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#Data -Becoming an AWS Policy Ninja using AWS IAM and AWS Organizations [SEC302]

SSRS APIs, M Queries, Power BI Desktop and more

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#Data -SSRS APIs, M Queries, Power BI Desktop and more

A Tour of Postgres Index Types

DZone Database Zone
A Tour of Postgres Index Types
A Tour of Postgres Index Types

At Citus, we spend a lot of time working with customers on data modeling, optimizing queries, and adding indexes to make things snappy. My goal is to be as available for our customers as we need to be in order to make you successful. Part of that is keeping your Citus cluster well-tuned and performant, which we take care of for you. Another part is helping you with everything you need to know about Postgres and Citus. After all, a healthy and performant database means a fast-performing app — and who wouldn’t want that? Today, we’re going to condense some of the information we’ve shared directly with customers about Postgres indexes.

Postgres has a number of index types, and with each new release seems to come with another new index type. Each of these indexes can be useful, but which one to use depends on the:

An Introduction to Caching: How and Why We Do It

DZone Database Zone
An Introduction to Caching: How and Why We Do It
An Introduction to Caching: How and Why We Do It

This article explores the offering of the various Java caching technologies out there that can play critical roles in improving application performance covering various scenarios.

Over the decades, information technology has been improving business processes drastically and has become a strategic solution for enterprises worldwide. What was once a "nice-to-have" is now a must-have. Applications are the core of any business and over recent years, their use has been augmented drastically. Therefore, response time has become even more significant. Data retrieval time plays a key role in user experience and is a critical requirement in almost all commercial applications. There are various factors affecting response time today, including network pipes, protocols, hardware, software, and internet speed. Vast IT infrastructure and ever-demanding system performance seriously undermine the strategic goals of any organization.

A Big Step Forward: Spring Data Neo4j 5.0 Release

DZone Database Zone
A Big Step Forward: Spring Data Neo4j 5.0 Release
A Big Step Forward: Spring Data Neo4j 5.0 Release

This post introduces what’s been happening in Spring Data Neo4j recently.

You will learn about the new features and the simplification of the programming model and find out what has changed under the covers, such as smarter querying for better performance. You will also read about the upcoming features. Don’t miss the opportunity to fill in the survey to bring your ideas into the roadmap!

Wednesday, October 18, 2017

Live Coding | Implementing Well Architected Operational Excellence

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#Data -Live Coding | Implementing Well Architected Operational Excellence

Complex Linq Queries in RavenDB 4.0

DZone Database Zone
Complex Linq Queries in RavenDB 4.0
Complex Linq Queries in RavenDB 4.0

With RQL in RavenDB 4.0, we have a whole new set of capabilities during queries. In the RC1 release of RavenDB, we had limited support for expressing the more complex queries in a strongly typed fashion using Linq. If you needed more complex queries, you had to drop to RQL strings. With the RC2 release, we bring you strongly typed and quite powerful queries using Linq. Let's see how this looks for a very simple query:

This isn’t really interesting, but it does show that we can do projections directly from the server side. Let's see something a bit more complex, shall we?

Dynamic labels in Power BI using DAX

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#Data -Dynamic labels in Power BI using DAX

Migrating Data in Couchbase From One Bucket to Another Using XDCR

DZone Database Zone
Migrating Data in Couchbase From One Bucket to Another Using XDCR
Migrating Data in Couchbase From One Bucket to Another Using XDCR

Couchbase provides XDCR, which makes your life simpler when it comes to data migration.

Following are my assumptions for this exercise.

How to Work With Pivot Tables in PostgreSQL, Amazon Redshift, BigQuery, and MS SQL Server

DZone Database Zone
How to Work With Pivot Tables in PostgreSQL, Amazon Redshift, BigQuery, and MS SQL Server
How to Work With Pivot Tables in PostgreSQL, Amazon Redshift, BigQuery, and MS SQL Server

All of us have at some point worked with some spreadsheet software, like Excel or Google Sheets, or BI tools and we have to admit that they offer certain functionalities that are very handy when it comes to data presentation and reporting, like the so-called pivot tables. Since many business applications require some sort of pivot tables, I am sure many of you have found themselves struggling with how to satisfy these requirements using a database instead of a spreadsheet.

Unfortunately, for many years, applying the pivot functionality to data in a database table was cumbersome. The main reason for this is that in a typical relational schema, tables are supposed to grow vertically rather than horizontally, repeating value in the same columns when necessary.

What Is Elasticsearch and How Can It Be Useful?

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What Is Elasticsearch and How Can It Be Useful?
What Is Elasticsearch and How Can It Be Useful?

Products that involve e-commerce and search engines with huge databases are facing issues such as product information retrieval taking too long. This leads to poor user experience and in turn turns off potential customers.

Lag in search is attributed to the relational database used for the product design, where the data is scattered among multiple tables — and the successful retrieval of meaningful user information requires fetching the data from these tables. The relational database works comparatively slow when it comes to huge data and fetching search results through database queries. Businesses nowadays are looking for alternatives where the data stored to promote quick retrieval. This can be achieved by adopting NoSQL rather than RDBMS for storing data. Elasticsearch (ES) is one such NoSQL distributed database. Elasticsearch relies on flexible data models to build and update visitor profiles to meet the demanding workloads and low latency required for real-time engagement.

Tuesday, October 17, 2017

AWS Public Sector Summit 2017 | Canberra: Keynote

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Cardinal Health: Moving Data to AWS in Real-time with Attunity

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Alert Logic Case Study — Amazon S3 — Cloud Storage

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Database Fundamentals #14: Modifying Data Through SSMS

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Database Fundamentals #14: Modifying Data Through SSMS
Database Fundamentals #14: Modifying Data Through SSMS

I've said it before, but I feel I should repeat myself. Using the SSMS GUI for data entry and data manipulation is not the preferred mechanism. T-SQL is the right way to manipulate the data in your database. For purposes of completion, though, I will show the GUI methods in this blog series.

Information doesn't go into the database and stay there, unchanged, forever. Data is modified. This occurs because information changes, such as when a person marries and changes their name, or information was incorrectly entered, in which case you need to fix it, or just about anything else. You have to have a mechanism for modifying existing information.

Learn How Goodwill Industries Ensures 24/7 Data Availability on AWS

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AWS Knowledge Center Videos: How do I associate an Elastic IP address with a WorkSpace?

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The New Database Connector in Mule 4

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The New Database Connector in Mule 4
The New Database Connector in Mule 4

There's a brand new Mule 4 Anypoint Connector for Database (DB) that you can use to connect to any relational database engine. Unlike other connectors such as File or FTP, this connector has a pretty similar UX compared to the one in Mule 3.x, with some considerable improvements, including:

Improved operations: Operations are streamlined and now simpler to use. We've extracted bulk functionality to their own set of operations so that you no longer have operations that change behaviors depending on the received payload. Dynamic queries simplified: There's now a single experience for executing static and dynamic queries. Embeddable transformations: You can now embed DataWeave transformations inside the insert/update operations so that you can construct the datasets you want to send to the DB without having a side effect on the message or using enrichers. Streaming simplified: You no longer have to worry about configuring streaming on your operations. The connector will use Mule's new streaming framework to handle that automatically. You can now even execute a select statement and process the results asynchronously without worrying about leaking connections!

Let's take a quick tour and see what's new.

51 Database Terms You Need to Know

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51 Database Terms You Need to Know
51 Database Terms You Need to Know

Lots of people talk about the exponential growth of data and how soon, we're going to have more data than we know what to do with. However, not as many people are talking about the database aspect to this — but they should be! As data grows, databases need to be able to keep up. That's why it's becoming increasingly important to not only understand how to analyze the growing amounts of data but also how to have databases that can handle it. That's why the DZone Editorial Team as aggregate a list of 51 database terms that you need to know if you're going to keep afloat with this overflow of data. (By the way, if you're interested in this, you might also be interested in our big data glossary!)

A

ACID (Atomicity, Consistency, Isolation, Durability): A term that refers to the model properties of database transactions, traditionally used for SQL databases.

CURL Comes to N1QL: Querying External JSON Data

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CURL Comes to N1QL: Querying External JSON Data
CURL Comes to N1QL: Querying External JSON Data

N1QL has many functions that allow you to perform a specific operation. One such function that has been added into the new Couchbase 5.0 DP is CURL.

CURL allows you to use N1QL to interact with external JSON endpoints; namely, Rest APIs that return results and data in JSON format. This function will allow N1QL to have a conservative set of curl functionality built into the language. Interaction primarily consists of data transfer to and from a server using the HTTP and HTTPS protocols. In short, the CURL function in N1QL provides you, the user, a subset of standard curl functionality within a query language.

Monday, October 16, 2017

The Expanding AWS and Salesforce Global Alliance

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M Intellisense, Bookmarks and more

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The Expanding AWS and Salesforce Global Alliance

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#Data -The Expanding AWS and Salesforce Global Alliance

GraphConnect New York 2017 Agenda: Everything You Need to Know

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GraphConnect New York 2017 Agenda: Everything You Need to Know
GraphConnect New York 2017 Agenda: Everything You Need to Know

You already have reasons why you should attend GraphConnect New York, and now you know who the must-see presenters will be. But now it’s time for the best reason to attend: the bottom-to-top agenda of all the keynotes, presentations, and lightning talks you can attend at the United States graph technology event of the year.

See the full agenda right here on GraphConnect.com or check out the highlights below!

Getting Started With Spring Data Cassandra

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Getting Started With Spring Data Cassandra
Getting Started With Spring Data Cassandra

I have recently been learning Apache Cassandra to use at work and I think it is about time I consolidated my experience within a blog post. But rather than focusing on how Cassandra works itself, this post will look at how to use Spring Data Cassandra.

I know I just said I wouldn’t focus on how Cassandra works, but if I don’t give you any sort of background information, you're going to feel incomplete. Apache Cassandra is a NoSQL distributed database for managing large amounts of data across many servers while providing high availability at the cost of decreased consistency. High availability is achieved by replicating data to multiple nodes, allowing one or many nodes to go down (the hamster stopped providing power to the machine) without stopping the system as a whole from working since there is still at least one node still running. Of course, if all the nodes stop working, then you're screwed and Cassandra won’t save you!

Back to the (SQL) Future

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Back to the (SQL) Future
Back to the (SQL) Future

In the first post in this series, I discussed the emergence of NoSQL to address the need to make databases compatible with cloud needs. And in my last blog post, I talked about the dichotomy between smart databases and smart applications. I asked whether we can have smart databases that can scale on the cloud. So now let's talk about why I think the answer is yes.

The big data revolution was substantially powered by Hadoop, initially a combination of a distributed store and the newfangled MapReduce query model. But in recent years, Hadoop has evolved from being the MapReduce alternative to SQL data warehouse technologies into a stack that strongly embraces SQL. In the big data analytics world, there has been a substantial return to SQL.

Sunday, October 15, 2017

What's New with AWS - Week of Oct 9, 2017

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Asyncio Tarantool Queue: Get in the Queue

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Asyncio Tarantool Queue: Get in the Queue
Asyncio Tarantool Queue: Get in the Queue

In this article, I’m going to pay specific attention to information processing using Tarantool queues. I’ll show the way that we use them to solve certain tasks and I will specifically describe our work with Tarantool Queue in Python with asyncio.

The Task of Notifying an Entire User Base

Mail.Ru runs several media sites, like News, Auto, Lady, Health, Hi-Tech, etc. Each one of them is visited by millions of users daily. The sites are adapted for mobile devices and the majority of them offer a touchscreen version. For the convenience of our users, we’ve created the News mobile application, which is quite popular on Android and iOS devices. Basically, when a “hot” piece of news is published, the user receives a push message. It goes something like this: the chief editor chooses a piece of news, presses “fire” on a management platform, and that’s it — go! But what next? We need to send out the news as quickly as possible to all subscribers.

Fun With SQL: Functions in Postgres

DZone Database Zone Fun With SQL: Functions in Postgres In our previous  Fun with SQL  post on the  Citus Data  blog, we covered w...