Apache Kafka is a distributed publish-subscribe messaging system. This article covers the architecture model, features and characteristics of Kafka framework and how it compares with traditional messaging systems.
Data modeling with Graph databases requires a different paradigm than modeling in Relational or other NoSQL databases like Document databases, Key Value data stores, or Column Family databases. InfoQ spoke with Jim Webber and Ian Robinson about data modeling efforts when using Graph databases.
Val Huber explains creating a RESTful API from an existing database schema, extending the API to define multi-table hierarchical resources, and adding behavior using declarative reactive expressions.
Scripting database objects change-scripts is a risky thing to automate. 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.
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