Concurrent will release Cascading 3.0 in early summer to allow certain applications to run on multiple Big Data frameworks including MapReduce, Tez, Spark, Storm and others. Additionally, Driven, the new commercial product from Concurrent, provides powerful enterprise data application management for Big Data applications.
Hortonworks announced the release of Hive 0.13 which marks the completion of the Stinger initiative. The new release also includes performance improvements as well as some new SQL features. Hive is an open source SQL Engine written on top of Hadoop that lets users query big data warehouses by writing SQL queries instead of MapReduce jobs.
Starting from the premise that today “80 percent of enterprise data is unstructured and growing at twice the rate of structured data”, Cloudera and MongoDB have announced a “strategic” partnership meant to provide customers the option to combine Cloudera’s Apache-based Big Data platform with MongoDB’s NoSQL solution.
The Internet of Things, Web APIs and Big Data will make continuous development a necessary reality and will tie developers down with maintenance work on completed applications, says Andrew Binstock of Dr. Dobbs. In that case, short sprints, continuous integration and deployment and modern programming practices are even more important to ensure a developer's time is better utilized.
DataBricks, the company behind Apache Spark, has announced a new addition into the Spark ecosystem called Spark SQL. Spark SQL is separate from Shark, and does not use Hive under the hood. InfoQ reached out to Reynold Xin and Michael Armbrust, software engineers at DataBricks, to learn more about Spark SQL.
Cloudera recently released the latest version of its software distribution, CDH5. Almost 20 months after the last major version, CDH4 seems like ages in the Big Data world. We take a look at new features this release brings and the future direction of Cloudera after the latest round of investment from Intel and Google Ventures.
The social-networking company AddThis open-sourced Hydra under the Apache version 2.0 License in a recent announcement. Hydra grew from an in-house platform created to process semi-structured social data as live streams and do efficient query processing on those data sets.
Spark users can now use a new Big Data platform provided by intelligence company Atigeo, which bundles most of the UC Berkeley stack into a unified framework optimized for low-latency data processing that can provide significant improvements over more traditional Hadoop-based platforms.
Apache released HBase 0.98 primarily addressing convergence with Apache Accumulo via cell-based security while resolving over 230 JIRA issues. These new security features are modeled after Accumulo.
Processing extremely large graphs has been and remains a challenge, but recent advances in Big Data technologies have made this task more practical. Tapad, a startup based in NYC focused on cross-device content delivery, has made graph processing the heart of their business model using Big Data to scale to terabytes of data.
Domino, a Platform-as-a-Service for data science, enables people to do analytical work using languages such as Python or R in the cloud (EC2).
According to a new Forrest report, Hadoop’s momentum is unstoppable. Its usage in the enterprise is continuously growing due to its ability to offer companies new ways to store, process, analyze, and share big data. The report takes a look at Hadoop vendors and ranks them.
At the Mobile World Congress, IBM has announced a developer contest for developers to create mobile consumer and business apps powered by IBM Watson cognitive computing platform. The winners of the IBM Watson Mobile Developer Challenge will receive design consulting and support from IBM to gain access to the market.
Recently, Spark graduated from the Apache incubator. Spark claims up to 100x speed improvements over Apache Hadoop over in-memory datasets and gracefully falling back to 10x speed improvement for on-disk performance. Based on Scala, it can run SQL queries and be used directly in R. It provides Machine Learning, Graph database capabilities and other further discussed in the article.