Databricks today announced the Apache Spark 2.0, available on it’s just in time platform. The company is established by the team that created Apache Spark. Databricks is the first company to offer Apache Spark 2.0 support. This is the first major release of open source Spark since it was updated to Spark 1.6 in 2015 was made possible as per the contribution of Databricks and the Spark team.
Reynold Xin Chief Architect and Cofounder of Databrick mentioned in a statement that they have spent hour’s eavesdropping to the Databrick users and members of the Spark community to improvise on our product. The Spark 2.0 is the product of a mixed experience of teams learning and user reviews and complaints.
Some notable features of the Spark 2.0 are Machine Learning Model Persistence, Speed, Simplicity, DataFrame-based Machine Learning APIs, Structured Streaming and Standard SQL Support.
Matei Zaharia, CTO, and Cofounder at Databricks said users accept and use the APIs we introduce very quickly and effectively and also provide with feedback which helps us to improve the Apache Spark. Databricks affords its users a full suite of tools to harness the open source 2.0 release and also ensure an end to end encryption. This gives the data scientists and engineers the coolest way to deploy Spark with evaluating data and progressive analytics.