Universal Format (UniForm)

Delta Universal Format (UniForm) allows you to read Delta tables with Iceberg clients.

UniForm takes advantage of the fact that both Delta Lake and Iceberg consist of Parquet data files and a metadata layer. UniForm automatically generates Iceberg metadata asynchronously, allowing Iceberg clients to read Delta tables as if they were Iceberg tables. You can expect negligible Delta write overhead when UniForm is enabled, as the Iceberg conversion and transaction occurs asynchronously after the Delta commit.

A single copy of the data files provides access to both format clients.


To enable UniForm, you must fulfill the following requirements:

  • The table must have column mapping enabled. See Delta column mapping.
  • The Delta table must have a minReaderVersion >= 2 and minWriterVersion >= 7.
  • Writes to the table must use Delta Lake 3.0 or above.

Enable Delta UniForm


Enabling Delta UniForm sets the Delta table feature IcebergCompatV1, a write protocol feature. Only clients that support this table feature can write to enabled tables. You must use Delta Lake 3.0 or above to write to Delta tables with this feature enabled.

The following table property enables UniForm support for Iceberg. iceberg is the only valid value.

'delta.universalFormat.enabledFormats' = 'iceberg'

You must also enable column mapping to use UniForm. This is set automatically during table creation if you enable UniForm. If you’re altering an existing table, you must set both table properties. The following examples demonstrate these options:

  'delta.universalFormat.enabledFormats' = 'iceberg');

  'delta.columnMapping.mode' = 'name',
  'delta.universalFormat.enabledFormats' = 'iceberg');


When you first enable UniForm, asynchronous metadata generation begins. This task must complete before external clients can query the table using Iceberg. See Check Iceberg metadata generation status.


You can turn off UniForm by unsetting the delta.universalFormat.enabledFormats table property. You cannot turn off column mapping once enabled, and upgrades to Delta Lake reader and writer protocol versions cannot be undone.


If you plan to use BigQuery as your Iceberg reader client, you must set spark.databricks.delta.write.dataFilesToSubdir to true on Delta Lake.

See Limitations.

When does UniForm generate Iceberg metadata?

Delta Lake triggers Iceberg metadata generation asynchronously after a Delta Lake write transaction completes using the same compute that completed the Delta transaction.

Iceberg can have significantly higher write latencies than Delta Lake. Delta tables with frequent commits might bundle multiple Delta commits into a single Iceberg commit.

Delta Lake ensures that only one Iceberg metadata generation process is in progress at any time in a single cluster. Commits that would trigger a second concurrent Iceberg metadata generation process successfully commit to Delta, but do not trigger asynchronous Iceberg metadata generation. This prevents cascading latency for metadata generation for workloads with frequent commits (seconds to minutes between commits).

Check Iceberg metadata generation status

UniForm adds the following properties to Iceberg table metadata to track metadata generation status:

Table property Description
converted_delta_version The latest version of the Delta table for which Iceberg metadata was successfully generated.
converted_delta_timestamp The timestamp of the latest Delta commit for which Iceberg metadata was successfully generated.

See documentation for your Iceberg reader client for how to review table properties outside Delta Lake. For Apache Spark, you can see these properties using the following syntax:


Read using a metadata JSON path

Some Iceberg clients allow you to register external Iceberg tables by providing a path to versioned metadata files. Each time UniForm converts a new version of the Delta table to Iceberg, it creates a new metadata JSON file.

Clients that use metadata JSON paths for configuring Iceberg include BigQuery. Refer to documentation for the Iceberg reader client for configuration details.

Delta Lake stores Iceberg metadata under the table directory, using the following pattern:


Delta and Iceberg table versions

Both Delta Lake and Iceberg allow time travel queries using table versions or timestamps stored in table metadata.

In general, Iceberg and Delta table versions do not align by either the commit timestamp or the version ID. If you wish to verify which version of a Delta table a given version of an Iceberg table corresponds to, you can use the corresponding table properties set on the Iceberg table. See Check Iceberg metadata generation status.



UniForm is read-only from an Iceberg perspective, though this cannot yet be enforced since UniForm uses file-system-based commits when writing Iceberg. If any external writer (not Delta Lake) writes to this Iceberg table, this may destroy your Delta table and cause data loss, as the Iceberg writer may perform data cleanup or garbage collection that Delta is unaware of.

The following limitations exist:

  • UniForm does not work on tables with deletion vectors enabled. See What are deletion vectors?.
  • Delta tables with UniForm enabled do not support LIST, MAP, and VOID types.
  • Iceberg clients can only read from UniForm. Writes are not supported.
  • Iceberg reader clients might have individual limitations, regardless of UniForm. See documentation for your target client.
  • Iceberg reader clients version 1.2.0 and below do not support INT96 timestamp type written by Apache Spark. Use the following code in notebooks that write to UniForm tables to avoid this limitation: spark.conf.set(“spark.sql.parquet.outputTimestampType”, “TIMESTAMP_MICROS”)

The following Delta Lake features work for Delta clients when UniForm is enabled, but do not have support in Iceberg:

  • Change Data Feed
  • Delta Sharing