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  • Metadata-Driven Design: Designing a Flexible Engine for API Data Retrieval

    by Aaron Kendall on  Apr 13, 2015

    Bulk data is commonly accessed via files & FTP. As the world moves toward APIs to facilitate collaboration, what are the requirements for data APIs? This article describes a meta-data driven architecture for bulk data ingestion. Two APIs operate in parallel to provide data changes as well as the data records themselves. An example demonstrates how API responses are parameterized using meta-data.

  • Highly Distributed Computations Without Synchronization

    by Christopher Meiklejohn on  Feb 17, 2015 1

    Synchronization of data across systems is expensive and impractical when running systems at scale. Traditional approaches for performing computations or information dissemination are not viable. In this article Basho Sr. Software Engineer Chris Meiklejohn explores the basic building blocks for crafting deterministic applications that guarantee convergence of data without synchronization.

  • Big Data Processing with Apache Spark – Part 1: Introduction

    by Srini Penchikala on  Jan 30, 2015 3

    Apache Spark is an open source big data processing framework built around speed, ease of use, and sophisticated analytics. In this article, Srini Penchikala talks about how Apache Spark framework helps with big data processing and analytics with its standard API. He also discusses how Spark compares with traditional MapReduce implementation like Apache Hadoop.

Building a Mars Rover Application with DynamoDB

Posted by Daniela Miao, Kenta Yasukawa on  Jan 25, 2015

This article shows how to use Amazon DynamoDB to create a Mars Rover application. You can use the same concepts described in this post to build your own web application. 1

The Definitive Guide to Database Version Control

Posted by Uri Margalit on  Dec 04, 2014

When it comes to database change, agility through automation - the ability to rapidly to accelerate delivery – is what differentiates world-class enterprises from the rest of the crowd. 4

Apache Ignite GridGain Incubator Project - Q&A Interview with Nikita Ivanov

Posted by Srini Penchikala on  Dec 03, 2014

GridGain announced that the In-Memory Data Fabric has been accepted into Apache Incubator program as Apache Ignite. InfoQ spoke with Nikita Ivanov about their product becoming part of Apache.

The Long Journey Towards Database Lifecycle Management

Posted by Ben Rees on  Nov 23, 2014

Application Lifecycle Management has traditionally been difficult for databases. Ben Rees, explains why the road ahead is now clear for Database Lifecycle Management.

Interview with Alex Holmes, author of “Hadoop in Practice. Second Edition”

Posted by Boris Lublinsky on  Nov 20, 2014

The new “Hadoop in Practice. 2 Edition" book by Alex Holmes covers a lot of topics building Hadoop code and organizing data to support code simplicity and execution speed.

Matt Schumpert on Datameer Smart Execution

Posted by Srini Penchikala on  Nov 13, 2014

Datameer, a big data analytics application for Hadoop, introduced Datameer 5.0 with Smart Execution to enhance the data analytics. InfoQ spoke with Matt Schumpert from Datameer about the new product.

Stats Anomalies Detector

Posted by Yonatan Harel and Ran Levy on  Nov 07, 2014

The article describes the general outline of the Stats Anomalies Detector developed at MyHeritage and provides a detailed explanation of how to enhance the code to meet your company’s needs.

SQL Server Source Control and Deployment with Visual Studio

Posted by Jonathan Allen on  Nov 04, 2014

The holy grail of database development is the ability to treat database objects as if they were normal source code. While SQL Server Data Tools doesn’t quite that level, it gets very close.

Analytics Across the Enterprise: How IBM Realizes Business Value from Big Data and Analytics

Posted by Alex Giamas on  Oct 27, 2014

"Analytics Across the Enterprise" book is a collection of experiences by analytics practitioners in IBM. InfoQ spoke with authors about lessons learned and IBM technologies in the Big Data area.

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