> For the complete documentation index, see [llms.txt](https://docs.e6data.com/query-engine/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.e6data.com/query-engine/guides/table-formats.md).

# Table formats

e6data supports table formats that define how data is stored, managed, and queried in a data lake or lakehouse environment. These are the table formats we support, and each table format provides a specific set of features based on its design and capabilities.

These formats offer advanced functionalities such as ACID transactions, schema and partition evolution, time travel, and efficient metadata handling.

<table><thead><tr><th width="196.06640625">Table Format</th><th>Description</th></tr></thead><tbody><tr><td><a href="/query-engine/guides/table-formats/delta-lake.md"><strong>Delta Lake</strong></a></td><td>Open-source storage layer that brings ACID transactions and scalable metadata handling to data lakes. Ideal for use cases requiring data reliability and consistency.</td></tr><tr><td><a href="/query-engine/guides/table-formats/iceberg.md"><strong>Apache Iceberg</strong></a></td><td>High-performance table format built for analytic datasets. Supports schema evolution, partitioning, and time travel without sacrificing performance.</td></tr><tr><td><a href="/query-engine/guides/table-formats/hive-tables.md"><strong>Hive tables</strong></a></td><td>Tables registered in a Hive Metastore (or compatible catalog) and stored in object storage. A common format for Hadoop- and Spark-based data lakes.</td></tr></tbody></table>


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