Audience
Organizations that want a unified analytics engine for large-scale data processing
About Apache Spark
Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources.
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Pricing
Free Version:
Free Version available.
Integrations
Company Information
Apache Software Foundation
Founded: 1999
United States
spark.apache.org
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Product Details
Platforms Supported
Cloud
Training
Documentation
Apache Spark Frequently Asked Questions
Apache Spark Product Features
Streaming Analytics
Data Enrichment
Supported
Data Wrangling / Data Prep
Supported
Multiple Data Source Support
Supported
Process Automation
Supported
Real-time Analysis / Reporting
Not Supported
Visualization Dashboards
Not Supported
