DataStax, the company that delivers Apache Cassandra to the enterprise, recently announced a partnership with Databricks, the company founded by the creators of Apache Spark. As the database industry’s first partnership to integrate Spark and Cassandra, DataStax and Databricks will deliver significantly faster analytics to users of both open source technologies and enable today’s most progressive businesses to deliver highly personalized online customer experiences.
Transactional Analytics Enable Dynamic Customer Experiences
Apache Cassandra is a fully distributed, highly scalable database that allows users to create online applications that are always on and can process large amounts of data in real time. Originally developed at UC Berkeley’s AMPLab, Apache Spark is a processing engine that enables applications in Hadoop clusters to run up to 100X faster in memory, and even 10X faster when running on disk. It also provides SQL, streaming data, machine learning, and graph computation functionality out-of-the-box as first class citizens to simplify building end-to-end analytic workflows. Together, these technologies can significantly boost analytics performance in a transactional database and allow companies to act quicker when serving customers’ needs.
Through this partnership, DataStax and Databricks are driving the operational database industry toward a better approach that allows companies to ingest user data at a very fast rate, and then analyze the results within the same distributed database. Responsiveness to customer needs is critical for successful online businesses, and by decreasing their “time to insights”, innovative companies such as video analytics provider Ooyala can create highly personalized experiences for their customers.
The integration of Spark and Shark with Cassandra is enabling Ooyala to efficiently and effectively store, analyze and process every piece of data powering our industry leading video analytics platform,” said Kelvin Chu, compute and data team lead, Ooyala. “With Cassandra as the data store and Spark for data crunching, these new analytic capabilities are making the processing of large data volumes a breeze. Spark on Cassandra is giving us the power to act on things in real-time, which means faster decisions and faster results for our ever-growing business.”
Cassandra Community Helps Drive Spark Adoption
The Cassandra community is growing quickly, with global user meetups increasing 400 percent over the past year and Spark serving as a frequent topic of discussion. DataStax employees already contribute the majority Apache Cassandra open source code contributions, and by working closely with Databricks engineers, will now contribute to the Spark community as well. The partnership will help spread adoption of both technologies while creating greater cohesiveness among users.
The Cassandra community has rapidly adopted Spark over the past year because it provides significantly faster analytics than Hadoop,” said Martin Van Ryswyk, executive vice president, engineering, DataStax. “We look forward to working closely with Databricks to make the best Spark on Cassandra solution available to the Spark community.”
Spark and Cassandra form a natural bond by combining blazing-fast analytics with a high-performance transactional database,” said Arsalan Tavakoli-Shiraji, head of business development, Databricks. “Additionally, all of Spark’s benefits, including a unified platform that seamlessly integrates SQL, streaming data and advanced analytics, will be natively available to Cassandra users. This is further validation of Spark’s emergence as a general Big Data processing engine with broader applications than just existing Hadoop clusters.”
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