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Amazon EMR is a managed AWS service for running Apache Spark, Hadoop, Hive, and related big-data frameworks on clusters or serverless infrastructure. It is designed for data engineers and analysts who need scalable batch processing, interactive analytics, and machine-learning workloads integrated with AWS storage and security services.
💡 Pick it for a polished lakehouse, collaborative notebooks, and integrated data science across major clouds.
Databricks is a unified data analytics platform that provides a collaborative environment for big data and machine learning.
Contact for pricing
💡 Choose it when your data already lives in Google Cloud and you want managed, open-source Spark processing.
Google Cloud Dataproc is a fast, easy-to-use, fully-managed cloud service for running Apache Spark and Apache Hadoop clusters.
Pricing varies based on usage
💡 Pick it if your organization is committed to Azure and needs managed Hadoop, Spark, Kafka, or HBase clusters.
Azure HDInsight is a cloud-based service from Microsoft that makes it easy to process big data and run Apache Hadoop, Spark, Kafka,...
Pricing varies based on the type of cluster and resources used.
💡 Choose it for serverless AWS ETL when you do not want to provision or tune Spark clusters.
AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it easy for customers to prepare and load...
Pricing based on usage
💡 Pick it for governed hybrid-cloud or on-premises data platforms where EMR's AWS focus is too restrictive.
Cloudera Data Platform is a unified platform for data engineering, data warehousing, machine learning, and analytics.
Contact for pricing
💡 Choose it for maximum control and portability when your team can operate Spark infrastructure itself.
Apache Spark is a unified analytics engine for big data processing, with built-in modules for streaming, SQL, machine learning, and graph processing.
Open-source
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