Databricks, a startup that has pushed the commercialization of the Apache Spark open-source big data software, today is announcing a $60 million funding round.
Databricks offers cloud service based on Spark that can be used for data integration, data pipelines, and other tasks. The Spark data processing engine is considered faster than Apache Hadoop, which companies like Cloudera, MapR, and publicly traded Hortonworks sell distributions of. Earlier this year, Hadoop-as-a-service startup Altiscale was acquired by SAP.
[aditude-amp id="flyingcarpet" targeting='{"env":"staging","page_type":"article","post_id":2132066,"post_type":"story","post_chan":"none","tags":null,"ai":false,"category":"none","all_categories":"big-data,business,dev,entrepreneur,","session":"B"}']NEA led the round, with participation from Andreessen Horowitz. Both firms also participated in Databricks’ previous funding round. To date, Databricks has raised $107.5 million.
Databricks was founded in 2013 and is based in San Francisco. Last year, it announced a partnership with IBM around machine learning capabilities in Spark.
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