Apache Spark

Apache Spark

Apache Software Foundation
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About

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.

About

PySpark is an interface for Apache Spark in Python. It not only allows you to write Spark applications using Python APIs, but also provides the PySpark shell for interactively analyzing your data in a distributed environment. PySpark supports most of Spark’s features such as Spark SQL, DataFrame, Streaming, MLlib (Machine Learning) and Spark Core. Spark SQL is a Spark module for structured data processing. It provides a programming abstraction called DataFrame and can also act as distributed SQL query engine. Running on top of Spark, the streaming feature in Apache Spark enables powerful interactive and analytical applications across both streaming and historical data, while inheriting Spark’s ease of use and fault tolerance characteristics.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Organizations that want a unified analytics engine for large-scale data processing

Audience

Application development solution for DevOps teams

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Not Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Supported
Free Trial Not Supported

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

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

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Reviews/Ratings

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

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

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

Company Information

PySpark
spark.apache.org/docs/latest/api/python/

Alternatives

Alternatives

dbt

dbt

dbt Labs
MLlib

MLlib

Apache Software Foundation
Apache Spark

Apache Spark

Apache Software Foundation
Spark Streaming

Spark Streaming

Apache Software Foundation

Categories

Big Data Supported
Data Analysis Supported
Data Modeling Supported
Query Engines Supported

Categories

Streaming Analytics Features

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

Integrations

Amazon SageMaker Data Wrangler Supported
Alluxio Supported
Apache Kudu Supported
Apache PredictionIO Supported
Apache Spark Not Supported
Baidu Sugar Supported
DataNimbus Supported
Equalum Supported
Foundational Supported
Great Expectations Supported
Hue Supported
IBM watsonx.data Supported
LakeSail Supported
Mage Dynamic Data Masking Supported
Prodea Supported
Tonic Supported
Vaultspeed Supported
VeloDB Supported
Yandex Data Proc Supported
doolytic Supported

Integrations

Amazon SageMaker Data Wrangler Supported
Alluxio Not Supported
Apache Kudu Not Supported
Apache PredictionIO Not Supported
Apache Spark Supported
Baidu Sugar Not Supported
DataNimbus Not Supported
Equalum Not Supported
Foundational Not Supported
Great Expectations Not Supported
Hue Not Supported
IBM watsonx.data Not Supported
LakeSail Not Supported
Mage Dynamic Data Masking Not Supported
Prodea Not Supported
Tonic Not Supported
Vaultspeed Not Supported
VeloDB Not Supported
Yandex Data Proc Not Supported
doolytic Not Supported
Claim Apache Spark and update features and information
Claim Apache Spark and update features and information
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