DataStax Rewires Hadoop with Apache Cassandra

DataStax, which has clients including entertainment companies such as Netflix as well as federal and financial organizations, recently unveiled Brisk, a new distribution that enhances the Hadoop and Hive platform with scalable low-latency data capabilities. Video interview with DataStax CEO Matt Pfeil.

At GigaOm's Structure Big Data conference, DataStax unveiled Brisk, a new distribution that enhances the Hadoop and Hive platform with scalable low-latency data capabilities. DataStax provides a commercial version of Apache Cassandra. Its new product, Brisk, provides a single platform that can server as a low-latency database for extremely high-volume web and real-time applications, while providing tightly coupled Hadoop and Hive analytics. Apache Cassandra, an open-source distributed database management system, is designed to store and allow very low-latency access to very large amounts of data spread out across many commodity servers while providing a highly available service with no single point of failure. The platform evolved from work at Google, Amazon and Facebook. "The challenge of 'big data' is two-fold," said Matt Pfeil, CEO and co-founder, DataStax. "The analytical side is well understood and served by Hadoop and Hive. However, we live in a real-time world, and the ability for applications to interact with big data at low-latency is equally important. Apache Cassandra was bred for big data, real-time scenarios, and using it to power Apache Hive and Apache Hadoop gives users a single solution that serves both needs." Pfeil explains more in this video shot in the expo area at Structure Big Data. This video runs about 1 minute, 45 seconds.

For additional videos, check out our DCK video archive and the Data Center Videos channel on YouTube.

Hide comments

Comments

  • Allowed HTML tags: <em> <strong> <blockquote> <br> <p>

Plain text

  • No HTML tags allowed.
  • Web page addresses and e-mail addresses turn into links automatically.
  • Lines and paragraphs break automatically.
Publish