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Databricks, the company whose founders created the Spark computing engine, is now adding a data storage piece to its cloud-based Spark computing service that combines management of data pipelines with management of data stored in columnar Parquet format in AWS S3 cloud storage.


  • Delta adds the missing data persistence piece to Databricks' Spark compute service.

Features and Benefits

  • Compares Databricks Delta with other cloud-based big data analytics services and data flow services.
  • Discusses how Databricks provides a good example of the growing role of data pipelines in changing how big data is analyzed and processed.

Key questions answered

  • How does Databricks Delta differentiate from cloud-based Hadoop services?
  • How does Databricks differentiate from other cloud-based data warehouses (e.g., Amazon Redshift, Snowflake) and query services (e.g., Amazon Athena) that have added direct access to cloud storage (e.g., AWS S3)?

Table of contents

Ovum view

  • Summary
  • Delta adds the missing data persistence to Spark compute service
  • Making the platform unified – Spark's missing links
  • Databricks must cultivate an unfamiliar audience: business analysts


  • Further reading
  • Author

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