We are now, simply, Redis
Integrates Redis Cloud with Databricks enabling users to accelerate Apache Spark analytics for real-time scenarios
Mountain View, June 7, 2016—Redis, the home of Redis, the world’s most popular in-memory NoSQL database, today announced it has integrated Redis Cloud (Redis’ fully managed enterprise Redis service) with Databricks’ just-in-time data platform powered by open source Apache Spark. The integration allows Databricks users using Redis Cloud to accelerate their Spark processes and SQL queries with enterprise grade Redis from Redis. The bi-directional cloud integration allows Redis Cloud’s 50,000+ users to both accelerate their Spark processes and SQL queries, and instantly run analytic processing on Redis data with the Databricks just-in-time data platform.
“Two of the most important and growing open source projects, Spark and Redis are collaborating to make the next generation of big data analysis real-time for instantaneous automated business decision making,” said Yiftach Shoolman, co-founder and CTO at Redis. “Analytics can now evolve from post-facto to inline and our joint customers can now gain insights from their data at lightning fast speeds.”
Using the power of Spark integrated with the real-time high performance of Redis, Redis Cloud users can use Spark for iterative processing of their data in Redis. Additionally, Databricks users can use Redis Cloud as a fast serving layer and accelerator for Spark processes and queries. Joint use cases for Spark and Redis include examples such as :
“Real-time is the name of the game for data scientists and developers in today’s complex big data web. This integration will enable data-minded professionals to continue using existing standard SQL-based analytics tools while enjoying the speeds of the two fastest in-memory processing technologies,” said Reynold Xin, cofounder and chief architect at Databricks.
Learn more with the following resources:
Redis at Spark Summit: https://redis.com/redis-labs-events
Getting Started with Redis Cloud on Databricks: https://databricks-prod-cloudfront.cloud.databricks.com
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