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  • Database Continuous Delivery

    The database creates a real challenge for automation, hence participation in continuous processes. Scripting database objects change-scripts into traditional version or using 'compare & sync' tools is either an inefficient or risky thing to automate, as the two concepts are unaware of the other. A better solution needs to be implemented in the shape of Continuous Delivery and DevOps for database.

  • MLConf NYC 2014 Highlights

    The MLConf conference was going strong in NYC on April 11th and was a full day packed with talks around Machine Learning and Big Data, featuring speakers from many prominent companies.

  • NoSQL, JSON, and Time Series Data Management: Interview with Anuj Sahni

    Time series data management is gaining more attention lately because the data is coming at us from all directions: sensors, mobile devices, Web tracking, financial events, factory automation, and utilities. InfoQ spoke with Anuj Sahni, Principal Product Manager at Oracle about the time series data and how to do data modeling for this type of data.

  • SQL Server 2014: NoSQL Speeds with Relational Capabilities

    For the last four years Microsoft has been working on the first rewrite of SQL Server’s query execution since 1998. The goal is to offer NoSQL-like speeds without sacrificing the capabilities of a relational database. At the heart of this is Hekaton, their memory optimized tables. While still accessible via traditional T-SQL operations, internally they are a fundamentally different technology.

  • Lambda Architecture: Design Simpler, Resilient, Maintainable and Scalable Big Data Solutions

    Lambda Architecture proposes a simpler, elegant paradigm designed to store and process large amounts of data. In this article, author Daniel Jebaraj presents the motivation behind the Lambda Architecture, reviews its structure with the help of a sample Java application.

  • Embedded Analytics and Statistics for Big Data

    This article provides an overview of tools and libraries available for embedded data analytics and statistics, both stand-alone software packages and programming languages with statistical capabilities. The authors also discuss how to combine and integrate these embedded analytics technologies to handle big data.

  • Big Data Analytics for Security

    In this article, authors discuss the role of big data and Hadoop in security analytics space and how to use MapReduce to efficiently process data for security analysis for use cases like Security Information and Event Management (SIEM) and Fraud Detection.

  • The Secrets of Database Change Deployment Automation

    Yaniv Yehuda looks at the challenges involved in automating database deployments and offer suggestions based on Agile and DevOps concepts.

  • Building Applications With Hadoop

    When building applications using Hadoop, it is common to have input data from various sources coming in various formats. In his presentation, “New Tools for Building Applications on Apache Hadoop”, Eli Collins overviews how to build better products with Hadoop and various tools that can help, such as Apache Avro, Apache Crunch, Cloudera ML and the Cloudera Development Kit.

  • ActiveJPA – Active Record Pattern for JPA

    ActiveJPA is a Java implementation of Martin Fowler’s Active Record pattern that wraps around JPA and provides useful abstractions to simplify data access. With ActiveJPA, models themselves act as a DAO and interact with the database without requiring additional code for the DAL. In this article the primary committer discusses ActiveJPA and provides plenty of usage examples.

  • Interview with Raffi Krikorian on Twitter's Infrastructure

    Raffi Krikorian, Vice President of Platform Engineering at Twitter, gives an insight on how Twitter prepares for unexpected traffic peaks and how system architecture is designed to support failure.

  • Preparing for Your First MongoDB Deployment: Backup and Security

    This article we focuses on the database backup tools and security policies when deploying MongoDB NoSQL databases. Topics like cloud backups with MongoDB Management Service (MMS), authentication, and authorization are covered.

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