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

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Ratings/Reviews

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Company Information

Apache Software Foundation
Founded: 1999
United States
spark.apache.org

Videos and Screen Captures

Apache Spark Screenshot 1
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Product Details

Platforms Supported
Cloud
Training
Documentation

Apache Spark Frequently Asked Questions

Q: What kinds of users and organization types does Apache Spark work with?
Q: What languages does Apache Spark support in their product?
Q: What other applications or services does Apache Spark integrate with?
Q: What type of training does Apache Spark provide?

Apache Spark Product Features

Big Data

Templates
Data Visualization
Collaboration
Data Blends
Data Cleansing
Data Warehousing
High Volume Processing
Data Mining
No-Code Sandbox
Predictive Analytics

Data Analysis

Data Visualization
Text Analytics
Regression Analysis
Data Discovery
Sentiment Analysis
High Volume Processing
Statistical Modeling
Predictive Analytics

Streaming Analytics

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards

Apache Spark Additional Categories