Compare - Databricks VS Apache Spark

Here’s the difference between Databricks and Apache Spark. The comparison is based on pricing, deployment, business model, and other important factors.

About Databricks

Databricks provides a data lakehouse that unifies your data warehousing and AI use cases on a single platform. With Databricks, you can implement a common approach to data governance across all data types and assets, and execute all of your workloads across data engineering, data warehousing, data streaming, data science, and machine learning on a single copy of the data. Built on open source and open standards, with hundreds of active partnerships, Databricks easily integrates with your modern data stack. Additionally, Databricks uses an open standards approach to data sharing to eliminate ecosystem restrictions. Finally, Databricks provides a consistent data platform across clouds to reduce the friction of multicloud environments. Today, Databricks has over 7000 customers, including Amgen, Walmart, Disney, HSBC, Shell, Grab, and Instacart.

About Apache Spark

Apache Spark is an open-source unified analytics engine for large-scale data processing. Spark provides an interface for programming entire clusters with implicit data parallelism and fault tolerance.

Comparison Table

Overview
CategoriesData Warehouses, Data LakesData Modelling and Transformation
StageLate StageLate Stage
Target SegmentEnterprise, Mid sizeMid Size, Enterprise
DeploymentSaaSOn Prem
Business ModelCommercialOpen Source
PricingFreemium, Contact SalesFreemium
LocationSan Francisco, USUS
Companies using it
Uber logoJMAN Group logoQuintoAndar logoAXS logoLucid logoGousto logoPluralsight logoAstrato Analytics logoInfoPrice logoCHONGTECHNOLOGIES logovmt pvt ltd logoCortex logonashtech global logoMatillion logosub-zero group, inc. logolegoai technologies logo
FOX logoPluralsight logostreamnative logoterality logoCircleUp logoInfoPrice logoCHONGTECHNOLOGIES logoFanatics Inc logoDashlane logoSelectDB logoApache Doris logodadosfera logo
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