Lakehouse platforms & table formats · Linux Foundation (originated by Databricks)

Delta Lake

Open-source storage format that brings ACID transactions and versioning to Parquet files on a data lake.

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Delta Lake is an open-source storage format, originally created by Databricks and now governed under the Linux Foundation, that layers a transaction log on top of Parquet files to bring database-style reliability to a data lake. It records every change to a table in an ordered, versioned log, which enables ACID transactions, time travel to earlier versions, schema enforcement and evolution, and safe concurrent reads and writes from multiple compute engines. Delta Lake underpins Databricks' lakehouse (and Microsoft Fabric's OneLake) but is also readable and writable by Spark, Trino, Flink, and other open-source engines outside Databricks. It is a library and specification rather than a hosted product: teams adopt it by pointing existing Spark or SQL workloads at Delta-formatted tables instead of raw Parquet.

At a glance

Vendor Linux Foundation (originated by Databricks)
Pricing model Open source + paid options
Free tier Yes
Deployment Self-hosted
Open source Yes (Apache-2.0)
Best for Spark-centric teams wanting reliable, versioned tables on a data lake without a separate warehouse.

Pricing

Free, open-source table format; no vendor pricing of its own, though Databricks and other lakehouse platforms charge separately for the compute that reads and writes Delta tables.

Pricing has not been verified yet — see the vendor's site.

Features

  • ACID transactions via an ordered transaction log
  • Time travel to query or roll back to prior table versions
  • Schema enforcement and controlled schema evolution
  • Concurrent batch and streaming reads/writes to the same table
  • Data compaction and Z-ordering for query performance
  • Change Data Feed for incremental downstream processing
  • Native support in Apache Spark, with connectors for Trino, Flink, and Presto

Integrations

Profile last reviewed September 21, 2026

Head to head

Alternatives

Apache Iceberg Open-source table format that adds warehouse-style transactions, schema evolution, and time travel to data-lake files. Apache Hudi Open-source table format optimized for high-volume upserts, deletes, and incremental data-lake pipelines. Apache Paimon Open-source lake table format built for unified streaming and batch updates, originating from the Apache Flink community.

Delta Lake in the index now

Terms to know

Data lakehouse A storage architecture that adds warehouse-style structure and transactions directly on top of low-cost data lake storage. Data lake A storage repository that holds raw data of any format cheaply, with structure applied only when the data is read. Data pipeline The automated sequence of steps that moves data from source systems to a destination, transforming it along the way. Apache Spark An open-source distributed computing engine for processing large datasets in parallel across a cluster of machines. Schema evolution The ability of a table to accommodate structural changes, like an added or renamed column, without breaking data.

Related guides

How to choose a lakehouse platform Choosing a lakehouse means two decisions, not one — which open table format your data sits in, and which platform manages and queries it.