{"id":2354,"date":"2017-10-02T09:00:45","date_gmt":"2017-10-02T13:00:45","guid":{"rendered":"https:\/\/solutionsreview.com\/data-integration\/?p=2354"},"modified":"2017-09-29T16:12:03","modified_gmt":"2017-09-29T20:12:03","slug":"actian-adds-native-spark-support-to-vector-in-hadoop","status":"publish","type":"post","link":"https:\/\/solutionsreview.com\/data-integration\/actian-adds-native-spark-support-to-vector-in-hadoop\/","title":{"rendered":"Actian Adds Native Spark Support to Vector in Hadoop"},"content":{"rendered":"
\"Actian

Source: Actian on Twitter<\/p><\/div>\n

Actian recently announced<\/a> Apache Spark support in an updated version of its Vector in Hadoop (VectorH) tool. The solution takes advantage of vectorized processing and in-memory acceleration for Hadoop data stores. The provider’s family of Vector analytic database offerings work on single server, cluster and hybrid transactional\/analytic environments both on-prem and in the cloud.<\/p>\n

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\"Download<\/a><\/p>\n<\/div>\n\t\t<\/div><\/div>\n

Analytic functionality included in VectorH is aimed at developers and data scientists that utilize Apache Spark. Some of Spark’s most noteworthy uses include machine learning, streaming, and prediction. VectorH in conjunction with Spark acts as a production platform that provides security, data updates in real-time, resource management, and query optimizers.<\/p>\n

A few highlights of Actian’s latest and greatest include:<\/p>\n