A Linux Foundation project since 2019, Delta Lake by Databricks is an independent project controlled by a development community rather than any single technology vendor. The Dell Validated Design for Analytics — Modern Data Stack enables reliable deployment and operation of Delta Lake in the solution. More than 150 developers from over 50 different organizations associated with Delta Lake working on multiple storage repositories are all engaged daily to help push the program goals forward. Key Delta Lake capabilities include:
- ACID transactions for Spark which bring serializable isolation levels that ensure readers always see consistent data
- Scalable metadata handling, through Spark’s distributed processing power, to easily handle all the metadata for petabyte-scale tables, with billions of files
- Streaming data ingest, batch historic backfill, and interactive queries that work by default with ease because Delta Lake tables are batch tables, a streaming source, and sink
- Schemas that are automatically enforced, handling schema variations to prevent insertion of bad records during ingestion
- Data versioning to enable rollbacks, full historical audit trails, and reproducible machine learning experiments
- Merge, update, and delete operations that allow easy handling of complex use cases like change-data-capture, slowly changing dimension (SCD) operations and streaming upserts