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.
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.
InfoQ spoke with Anuj Sahni, Principal Product Manager at Oracle about the time series data, NoSQL databases and best practices for managing this type of data.
For the last four years MS has been working on the first rewrite of SQL Server’s query execution since 1998. The goal is to offer NoSQL-like speeds with the capabilities of a relational database. 2
Lambda Architecture proposes a simpler, elegant paradigm designed to process large amounts of data. In this article, author discusses Lambda Architecture with the help of a sample Java application. 6
This article provides an overview of tools and libraries available for embedded data analytics & statistics, both stand-alone software packages and programming languages with statistical capabilities.
In this article, authors discuss the role of big data and Hadoop in security analytics space and how to use MapReduce to process data for security analysis.
Yaniv Yehuda looks at the challenges involved in automating database deployments and offer suggestions based on Agile and DevOps concepts. 6
How to use various tools such as Apache Avro, Apache Crunch, Cloudera ML and the Cloudera Development Kit to build applications that use Hadoop.
ActiveJPA is a Java implementation of Martin Fowler’s Active Record over JPA and provides abstractions to simplify data access. In this article the primary committer illustrates ActiveJPA usage 7
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. 1
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