Delta Lake
Delta Lake is a free, open-source storage framework for building lakehouse architectures on data lakes.
What Delta Lake is
Delta Lake is a free, open-source storage framework for building lakehouse architectures on data lakes. It stores tables for use with compatible compute engines across cloud, on-premises, and local environments. Serializable ACID transactions protect consistency, while schema enforcement and evolution help manage changes to table data. SQL, Scala/Java, and Python APIs support merge, update, and delete operations. Delta Lake combines batch and streaming workloads with exactly-once ingestion semantics, and table-level time travel lets users inspect or restore earlier versions for audits, rollbacks, or reproducibility. Its scalable metadata is designed for petabyte-scale tables with billions of partitions and files. Delta Universal Format lets Iceberg and Hudi clients read Delta tables. Listed integrations and compatible engines include Spark, Flink, Hive, Trino, Athena, BigQuery, Databricks, Microsoft Fabric, Snowflake in beta, PrestoDB, and Redshift. The independent project is governed through the Linux Foundation Projects. Users bring their own storage backend, and deployment can be self-hosted or otherwise arranged. Delta Lake releases are compatible with specified Apache Spark versions.
Good
- Serializable ACID transactions protect consistency.
- Table time travel supports audits and rollbacks.
- Supports batch and streaming workloads.
- Iceberg and Hudi clients can read Delta tables.
Watch out
- Users bring their own storage backend.
- Releases must match specified Apache Spark versions.
- ClickHouse integration is read-only for existing S3 tables.
Who it suits
Delta Lake may suit teams building data lakehouses that need transactional tables, schema controls, or both batch and streaming workflows. It is intended for use with compatible query and compute engines across cloud, on-premises, and local environments.
Verdict
Delta Lake provides table storage features and data operations for lakehouse architectures, with broad listed engine compatibility. Check the Spark version requirements and the read-only limit on the described ClickHouse integration before choosing an implementation.
Plans and prices
From Delta Lake's own pricing page, checked 7 Oct 2026.
| Plan | Price | What it gives you |
|---|---|---|
| Delta Lake | Free | Open-source storage framework; use with compatible compute engines and platforms |
The facts
Each one read from Delta Lake's own pages, with the date it was checked.
What it does
- ACID transactions
- Delta Lake provides serializable transactions to protect data consistency.checked 7 Oct 2026
- Batch and streaming
- Delta Lake supports unified batch and streaming workloads with exactly-once ingestion semantics.checked 7 Oct 2026
- Community support
- The project points users to Slack, GitHub Issues, Stack Overflow, and Google Groups for community help.checked 7 Oct 2026
- Compatibility requirement
- Delta Lake releases are compatible with specified Apache Spark versions; for example, the releases page lists Delta Lake 4.3.x with Spark 4.0.x and 4.1.x.checked 7 Oct 2026
- Compute engines
- The site lists Spark, PrestoDB, Flink, Trino, Hive, Snowflake, Google BigQuery, Athena, Redshift, Databricks, and Azure Fabric among compatible compute engines.checked 7 Oct 2026
- Data changes
- SQL, Scala/Java, and Python APIs support merge, update, and delete operations on datasets.checked 7 Oct 2026
- Data operations
- Delta Lake provides SQL, Scala/Java, and Python APIs to merge, update, and delete datasets.checked 7 Oct 2026
- Governance
- Delta Lake is an independent open-source project governed through the Linux Foundation Projects and is not controlled by a single company.checked 7 Oct 2026
- Integration example
- The integrations page says Apache Spark can read from and write to Delta Lake.checked 7 Oct 2026
- Integration limit
- The integrations page describes its ClickHouse integration as read-only for existing Delta Lake tables in Amazon S3.checked 7 Oct 2026
- Integrations
- Listed integrations include Apache Spark, Flink, Hive, Trino, Athena, BigQuery, Databricks, Microsoft Fabric, and Snowflake (Beta).checked 7 Oct 2026
- Interoperability
- Delta Universal Format lets Iceberg and Hudi clients read Delta tables.checked 7 Oct 2026
- Open format
- Delta Universal Format (UniForm) lets Iceberg and Hudi clients read Delta tables.checked 7 Oct 2026
- Project governance
- Delta Lake is an independent open-source project that the site says is not controlled by any single company and joined the Linux Foundation Projects in 2019.checked 7 Oct 2026
- Scalable metadata
- The project says it can handle petabyte-scale tables with billions of partitions and files.checked 7 Oct 2026
- Schema controls
- Schema evolution and enforcement help prevent bad data from causing corruption.checked 7 Oct 2026
- Sharing limit
- Delta Sharing reads support batch, streaming, and table changes, but writing to a shared table is not supported.checked 7 Oct 2026
- Table scale
- Its scalable metadata feature is described as handling petabyte-scale tables with billions of partitions and files.checked 7 Oct 2026
- Time travel
- Users can access or revert to earlier data versions for audits, rollbacks, or reproducibility.checked 7 Oct 2026
- Transactions
- Delta Lake supports ACID transactions and serializability, which the site describes as the strongest level of isolation.checked 7 Oct 2026
- What it does
- Delta Lake is an open-source storage framework for building format-agnostic lakehouse architectures on data lakes.checked 7 Oct 2026
- What it is
- Delta Lake is an open-source storage framework for building format-agnostic lakehouse architectures.checked 7 Oct 2026
- Who it is for
- The project describes Delta Lake as usable with query engines across cloud, on-premises, and local environments.checked 7 Oct 2026
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