Amazon EMR vs. PySpark Comparison


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About Amazon EMR is the industry-leading cloud big data platform for processing vast amounts of data using open-source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto. With EMR you can run Petabyte-scale analysis at less than half of the cost of traditional on-premises solutions and over 3x faster than standard Apache Spark. For short-running jobs, you can spin up and spin down clusters and pay per second for the instances used. For long-running workloads, you can create highly available clusters that automatically scale to meet demand. If you have existing on-premises deployments of open-source tools such as Apache Spark and Apache Hive, you can also run EMR clusters on AWS Outposts. Analyze data using open-source ML frameworks such as Apache Spark MLlib, TensorFlow, and Apache MXNet. Connect to Amazon SageMaker Studio for large-scale model training, analysis, and reporting.	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 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 Companies that want to easily run and scale Apache Spark, Hive, Presto, and other big data frameworks	Audience Application development solution for DevOps teams
Support Phone Support Not Supported 24/7 Live Support Not Supported Online 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 View more images or videos	Screenshots and Videos View more images or videos
Pricing No information available. Free Version Not 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 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	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 Amazon Founded: 1994 United States aws.amazon.com/emr/	Company Information PySpark spark.apache.org/docs/latest/api/python/
Alternatives AWS Glue Amazon	Alternatives pandas
Amazon Athena Amazon	Polars
Cloudera	Tumult Analytics
E-MapReduce Alibaba	Apache Spark Apache Software Foundation
Apache Spark Apache Software Foundation View All	Spark Streaming Apache Software Foundation View All
Categories Big Data Supported	Categories Application Development Supported Query Engines Supported

Integrations Amazon SageMaker Data Wrangler Supported Apache Spark Supported Feast Supported Tecton Supported AWS App Mesh Supported AWS Data Pipeline Supported AWS Step Functions Supported Amazon SageMaker Unified Studio Supported Gurucul Supported Hadoop Supported Immuta Supported MetricFire Supported Protegrity Supported Quorso Supported Service Center Supported Tonic Ephemeral Supported Unravel Supported Veza Supported Zepl Supported definity Supported Show More Integrations View All 48 Integrations	Integrations Amazon SageMaker Data Wrangler Supported Apache Spark Supported Feast Supported Tecton Supported AWS App Mesh Not Supported AWS Data Pipeline Not Supported AWS Step Functions Not Supported Amazon SageMaker Unified Studio Not Supported Gurucul Not Supported Hadoop Not Supported Immuta Not Supported MetricFire Not Supported Protegrity Not Supported Quorso Not Supported Service Center Not Supported Tonic Ephemeral Not Supported Unravel Not Supported Veza Not Supported Zepl Not Supported definity Not Supported Show More Integrations View All 7 Integrations
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