Hadoop software and services firm Hortonworks says the plans it outlined today for Apache Spark are designed to make the in-memory engine a better candidate for enterprise use. The company is ...

Spark is the ... sources such as Hadoop Distributed File System, NoSQL databases, or relational data stores like Apache Hive. This framework also supports In-memory processing, which increases ...

That’s because structured data conforms nicely to a fixed schema model of neat columns and rows that can be manipulated using ... Apache Spark is a high-performance, distributed data processing ...

BigDL is a distributed ... Spark can process data from a variety of sources, including the HDFS, Apache Cassandra*, or Apache Hive*. Its high performance comes from ability to do in-memory ...

To work at the speed of Spark’s continuous processing, you need to augment it with a high-speed streaming database like Redis. This open source in-memory ... time using Redis and Apache Spark.

Apache Spark is getting ... RDD with the Hazelcast in-memory grid are designed to serve as the basis for improved distributed computing required for large datasets. “Any big data solution needs to be ...

either distributed or on single node. So it will orchestrate multiple engines to get the job done.” Datameer wrote its own in-memory processing layer instead of using Spark, but it’s a strong ...

A little-known startup called Hazelcast Inc. is hoping to steal some of the limelight from popular open-source projects Apache Spark and ... and lower-latency distributed processing engine for ...

offering for the first time in-memory processing via the Apache Spark open-source engine. The use of Spark in DataStax Enterprise 4.5, now on general availability, also means the database offers ...

Apache Spark and Apache Hadoop are both popular, open-source data science tools offered by the Apache Software Foundation. Developed and supported by the community, they continue to grow in ...