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Ilum is an open-source data platform for running and managing Apache Spark workloads on Kubernetes. It is designed for data engineers and platform teams that need self-hosted big-data processing with job management, notebooks, and SQL access.
💡 Pick it for a managed, enterprise-grade lakehouse with Spark, governance, and machine learning in one platform.
Databricks is a unified data analytics platform that provides a collaborative environment for big data and machine learning.
Contact for pricing
💡 Pick it if your data stack already runs on AWS and you want managed Spark with elastic infrastructure.
Amazon EMR is a managed AWS service for running Apache Spark, Hadoop, Hive, and related big-data frameworks on clusters or serverless infrastructure....
Usage-based; EMR and AWS infrastructure billed separately
💡 Pick it for Google Cloud-native Spark workloads connected to BigQuery and Cloud Storage.
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 when hybrid-cloud governance, compliance, and on-premises data support matter more than simplicity.
Cloudera is an enterprise data cloud company that provides a modern platform for machine learning and analytics optimized for the cloud.
Contact for pricing
💡 Pick it for SQL-first lakehouse analytics and Iceberg support rather than primarily managing Spark applications.
Dremio is a lakehouse query and semantic layer platform that provides SQL access across data lakes, warehouses, and other sources. It is...
Free community edition; paid cloud and enterprise plans
💡 Pick it if you want the underlying open-source Spark engine and are willing to assemble the surrounding platform yourself.
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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