Databricks SQL release notes 2026

The following Databricks SQL features and improvements were released in 2026.

May 2026

Databricks SQL version 2026.15 is now available in Preview

May 26, 2026

Databricks SQL version 2026.15 is now available in the Preview channel. Review the following section to learn about new features, behavioral changes, and bug fixes.

XPath no longer fetches external DTDs

When you evaluate xpath over XML, Azure Databricks no longer loads external Document Type Definitions (DTDs) declared in the document. Previously, XPath could fail when the XML contained an external DTD reference that pointed to a malformed URL or an unreachable endpoint. Because DTD validation is separate from XPath evaluation, queries that already succeeded return the same results as before. Queries that previously failed only during external DTD retrieval can now succeed.

NULL struct preservation in INSERT, MERGE, and streaming writes with schema evolution

For INSERT, MERGE, and streaming writes that use schema evolution, a NULL struct in the source is now stored as NULL in the target. Previously, that value was incorrectly materialized as a non-null struct with every field set to NULL, while the same operations without schema evolution preserved NULL structs correctly. If your code relied on receiving a non-null struct whose fields were all NULL, update your code to handle a NULL struct instead.

NullType (VOID) support in Delta tables

Delta Lake tables now support VOID columns. Previously, VOID columns were silently skipped by path-based DataFrame reads and time travel queries. These queries now include VOID columns in the output. Writes are unaffected. See VOID type for restrictions on where VOID columns can appear in the schema.

Review any queries that read from Delta Lake tables with VOID columns to verify they handle the additional columns correctly. Queries that depend on column count or position, such as INSERT INTO ... SELECT *, might start failing after the upgrade. In particular, certain INSERT queries with schema evolution enabled might silently shift data into the wrong columns.

SHOW CREATE TABLE supports metric views

SHOW CREATE TABLE now supports metric views. Previously, running this command on a metric view raised an error. The output for metric views includes the fully qualified three-part name with catalog (for example, CREATE VIEW catalog.db.my_metric_view ...), making it easier to recreate the metric view in the correct location.

Fix for LEFT OUTER JOIN LATERAL dropping rows

A bug that incorrectly dropped rows from LEFT OUTER JOIN LATERAL queries is now fixed. Queries using this construct now return the correct results. To temporarily revert to the previous behavior, set spark.databricks.sql.optimizer.lateralJoinPreserveOuterSemantic to true.

NATURAL JOIN respects case-insensitive column matching

NATURAL JOIN now correctly uses case-insensitive column matching when spark.sql.caseSensitive is set to false (the default). Previously, NATURAL JOIN used case-sensitive comparison to identify common columns, causing columns that differed only in case (for example, ID versus id) to not be recognized as matching. This caused NATURAL JOIN to silently produce cross-join results. Queries affected by this bug now return correct results with properly joined columns.

SQL UDF dependency validation in Unity Catalog

Unity Catalog now enforces dependency validation for SQL user-defined functions (UDFs) to prevent access control bypass. Previously, SQL functions created through the REST API could reference dependencies the user did not have access to. SQL UDFs with invalid dependency configurations are now blocked from execution.

Optimized writes for partitioned Unity Catalog tables created with CRTAS

Optimized writes are now correctly applied to partitioned Unity Catalog tables created with CREATE OR REPLACE TABLE ... AS SELECT (CRTAS). Previously, CRTAS on new partitioned Unity Catalog tables did not apply optimized writes, resulting in a higher number of small files per partition. This fix can increase write latency. To revert to the previous behavior, set spark.databricks.delta.optimizeWrite.UCTableCRTAS.enabled to false.

Fix incorrect EPSG authority for ESRI-defined SRID 102100

The Coordinate Reference System (CRS) mapping for SRID 102100 now correctly uses ESRI:102100 instead of the incorrect EPSG:102100. This fix ensures geospatial data is stored with the correct authority for better interoperability with other systems.

CREATE OR REPLACE support for temporary tables

CREATE OR REPLACE TEMP TABLE syntax is now supported, allowing you to create or replace temporary tables in a single statement. This eliminates the need to explicitly drop and recreate temporary tables.

Delta table history includes write option flags

Delta Lake table history (DESCRIBE HISTORY) now includes write option flags in the operationParameters column for WRITE and REPLACE TABLE operations. When the following options are explicitly enabled, they appear as Boolean flags in the history (only included when true):

For WRITE and REPLACE TABLE operations:

  • isDynamicPartitionOverwrite: present when dynamic partition overwrite mode was used
  • canOverwriteSchema: present when schema overwrite (overwriteSchema) was enabled
  • canMergeSchema: present when schema merge (mergeSchema) was enabled

For REPLACE TABLE operations:

  • predicate: present when replaceWhere was used
  • isV1WriterSaveAsTableOverwrite: present when the replace was triggered by a .saveAsTable overwrite

New geospatial functions

The following geospatial functions are now available:

Improved spatial join support

The ST_DWithin (distance within) predicate is now supported as a join condition for spatial joins. Conjunctions of predicates are now eligible for spatial joins, for example condition AND st_predicate.

Native data profiling for results tables in the SQL editor

May 1, 2026

You can now view profiling statistics for columns in results tables in the new Databricks SQL editor. Select column headers and click Sidebar icon. Open selection details to view profiling statistics.

April 2026

agg SQL function as a synonym for measure

April 30, 2026

The new agg aggregate function is a synonym for measure. Use agg(measure_column) as a shorter alternative when querying measures in a metric view.

Databricks SQL version 2026.10 is rolling out in Current

April 23, 2026

Databricks SQL version 2026.10 is rolling out to the Current channel. See features in 2026.10.

March 2026

Databricks SQL version 2026.10 is now available in Preview

March 26, 2026

Databricks SQL version 2026.10 is now available in the Preview channel. Review the following section to learn about new features, behavioral changes, and bug fixes.

Observation metric errors no longer fail queries

Errors during observation metric collection no longer cause query execution failures. Previously, errors in OBSERVE clauses (such as division by zero) could block or fail the entire query. Now, the query completes successfully and the error is raised when you call observation.get.

Optimized writes for Unity Catalog CRTAS operations

CREATE OR REPLACE TABLE AS SELECT (CRTAS) operations on partitioned Unity Catalog tables now apply optimized writes by default, producing fewer, larger files. To disable, set spark.databricks.delta.optimizeWrite.UCTableCRTAS.enabled to false.

Timestamp partition values use session timezone

Timestamp partition values now use the SQL warehouse session timezone. If you have timestamp partitions written before Databricks SQL version 2025.40, run SHOW PARTITIONS to verify your partition metadata before writing new data.

DESCRIBE FLOW reserved keyword

The DESCRIBE FLOW command is now available. If you have a table named flow, use DESCRIBE schema.flow, DESCRIBE TABLE flow, or DESCRIBE `flow` with backticks.

SpatialSQL boolean set operations

ST_Difference, ST_Intersection, and ST_Union use a new implementation with the following improvements:

  • Valid input geometries always produce a result and no longer raise errors. Invalid inputs don't raise errors but might not produce valid results.
  • Approximately 2x faster performance.
  • Results can differ after the 15th decimal place for line-segment intersections due to different formulas and order of operations.
  • Results are normalized for consistent, comparable output:
    • Points are sorted by coordinate values.
    • Linestrings are built from the longest possible paths.
    • Polygon rings are rotated so the first point has the smallest coordinate values.
  • This normalization applies in all cases except when calling ST_Difference with two non-overlapping geometries, where the first geometry is returned unmodified.

Exception types for SQLSTATE

Exception types now support SQLSTATE. If your code parses exceptions by string matching or catches specific exception types, update your error handling logic.

DATETIMEOFFSET data type support for Microsoft Azure Synapse

The DATETIMEOFFSET data type is now available for Microsoft Azure Synapse connections.

Google BigQuery table comments

Google BigQuery table descriptions are resolved and exposed as table comments.

Schema evolution with INSERT statements

Use the WITH SCHEMA EVOLUTION clause with SQL INSERT statements to automatically evolve the target table's schema during insert operations. The clause is supported for INSERT INTO, INSERT OVERWRITE, and INSERT INTO ... REPLACE forms. For example:

INSERT WITH SCHEMA EVOLUTION INTO students TABLE visiting_students_with_additional_id;

The target Delta Lake table's schema is updated to accommodate additional columns or widened types from the source. For details, see schema evolution and INSERT statement syntax.

Preserved NULL struct values in INSERT operations

INSERT operations with schema evolution or implicit casting now preserve NULL struct values when the source and target tables have differing struct field orders.

parse_timestamp SQL function

The parse_timestamp SQL function parses timestamp strings using multiple patterns and runs on the Photon engine for improved performance when parsing timestamps in multiple formats. See Datetime patterns for information about datetime pattern formatting.

max_by and min_by with optional limit

The aggregate functions max_by and min_by now accept an optional third argument limit (up to 100,000). When provided, the functions return an array of up to limit values corresponding to the largest (or smallest) values of the ordering expression, simplifying top-K and bottom-K queries without window functions or CTEs.

Period-over-period window measures with offset

Window measures in metric views support an offset field that shifts the window frame backward or forward along the order dimension by a fixed interval. Use offset to define period-over-period measures such as year-over-year or month-over-month. See How offset shifts the window frame.

Include or exclude the anchor row in trailing and leading window measures

The trailing and leading range values for window measures accept an optional inclusive or exclusive modifier that controls whether the anchor row is part of the rolling window. The default is exclusive, which matches previous behavior. See Include or exclude the anchor row.

Vector aggregate and scalar functions

New SQL functions operate on ARRAY<FLOAT> vectors for embedding and similarity workloads:

Aggregate functions:

  • vector_avg: Returns the element-wise average of vectors in a group.
  • vector_sum: Returns the element-wise sum of vectors in a group.

Scalar functions:

See Built-in functions.

SQL cursor support in compound statements

SQL scripting compound statements now support cursor processing. Use DECLARE CURSOR to define a cursor, then OPEN statement, FETCH statement, and CLOSE statement to run the query and consume rows one at a time. Cursors can use parameter markers and condition handlers such as NOT FOUND for row-by-row processing.

Approximate top-k sketch functions

New functions enable building and combining approximate top-K sketches for distributed top-K aggregation:

For more information, see approx_top_k aggregate function and Built-in functions.

Tuple sketch functions

New aggregate and scalar functions for tuple sketch support distinct counting and aggregation over key-summary pairs.

Aggregate functions:

Scalar functions:

See Built-in functions.

Custom dependencies for Unity Catalog Python UDTFs

Unity Catalog Python user-defined table functions (UDTFs) can now use custom dependencies for external libraries, so you can use packages beyond what's available in the default SQL warehouse environment. See Extend UDFs using custom dependencies.

New geospatial functions

The following geospatial functions are now available:

  • st_estimatesrid function: Estimates the best projected spatial reference identifier (SRID) for an input geometry.
  • st_force2d function: Converts a geography or geometry to its 2D representation.
  • st_nrings function: Counts the total number of rings in a polygon or multipolygon, including both exterior and interior rings.
  • st_numpoints function: Counts the number of non-empty points in a geography or geometry.

Photon support for geospatial functions

The following geospatial functions now run on the Photon engine for faster performance:

February 2026

Databricks SQL version 2025.40 is rolling out in Current

February 23, 2026

Databricks SQL version 2025.40 is rolling out to the Current channel. See features in 2025.40.

Databricks SQL version 2025.40 is now available in Preview

February 11, 2026

Databricks SQL version 2025.40 is now available in the Preview channel. Review the following section to learn about new features, behavioral changes, and bug fixes.

SQL scripting is generally available

SQL scripting is now generally available. Write procedural logic with SQL, including conditional statements, loops, local variables, and exception handling.

Parameter markers now supported in more SQL contexts

You can now use named (:param) and unnamed (?) parameter markers anywhere a literal value of the appropriate type is allowed. This includes DDL statements such as CREATE VIEW v AS SELECT ? AS c1, column types such as DECIMAL(:p, :s), and comments such as COMMENT ON t IS :comment. This allows you to parameterize a large variety of SQL statements without exposing your code to SQL injection attacks. See Parameter markers.

IDENTIFIER clause expanded to more SQL contexts

The IDENTIFIER clause, which casts strings to SQL object names, is now supported in nearly every context where an identifier is permitted. Combined with expanded parameter marker and literal string coalescing support, you can parameterize anything from column aliases (AS IDENTIFIER(:name)) to column definitions (IDENTIFIER(:pk) BIGINT NOT NULL). See IDENTIFIER clause.

Literal string coalescing supported everywhere

Sequential string literals such as 'Hello' ' World' now coalesce into 'Hello World' in any context where string literals are allowed, including COMMENT 'This' ' is a ' 'comment'. See STRING type.

New BITMAP_AND_AGG function

A new BITMAP_AND_AGG function is now available to complement the existing library of BITMAP functions.

New Theta Sketch functions for approximate distinct counts

A new library of functions for approximate distinct count and set operations using Datasketches Theta Sketch is now available:

New KLL Sketch functions for approximate quantiles

A new library of functions for building KLL Sketches for approximate quantile computation is now available:

You can merge multiple KLL sketches in an aggregation context using kll_merge_agg_bigint, kll_merge_agg_double, and kll_merge_agg_float.

SQL window functions in metric views

You can now use SQL window functions in metric views to calculate running totals, rankings, and other window-based calculations.

New geospatial functions

The following new geospatial functions are now available:

EWKT input support for existing geometry and geography functions

The following functions now accept Extended Well-Known Text (EWKT) as input:

Improved performance for repeated queries over tables with row filters and column masks

Repeated eligible queries over tables with row filters and column masks now benefit from improved query result caching, resulting in faster execution times.

Improved geospatial function performance

Spatial join performance is improved with shuffled spatial join support. The following ST functions now have Photon implementations:

FSCK REPAIR TABLE includes metadata repair by default

FSCK REPAIR TABLE now includes an initial metadata repair step before checking for missing data files, allowing it to work on tables with corrupt checkpoints or invalid partition values. Additionally, the dataFilePath column in the FSCK REPAIR TABLE DRY RUN output schema is now nullable to support new issue types where the data file path is not applicable.

DESCRIBE TABLE output includes metadata column

The output of DESCRIBE TABLE [EXTENDED] now includes a metadata column for all table types. This column contains semantic metadata (display name, format, and synonyms) defined on the table as a JSON string.

NULL structs preserved in MERGE, UPDATE, and streaming write operations

NULL structs are now preserved as NULL in Delta Lake MERGE, UPDATE, and streaming write operations that include struct type casts. Previously, NULL structs were expanded to structs with all fields set to NULL.

Partition columns materialized in Parquet files

Partitioned Delta Lake tables now materialize partition columns in newly written Parquet data files. Previously, partition values were stored only in the Delta Lake transaction log metadata. Workloads that directly read Parquet files written by Delta Lake sees additional partition columns in newly written files.

Timestamp partition values respect session timezone

Timestamp partition values are now correctly adjusted using the spark.sql.session.timeZone configuration. Previously, they were incorrectly converted to UTC using the JVM timezone.

Time travel restrictions updated

Azure Databricks now blocks time travel queries beyond the deletedFileRetentionDuration threshold for all tables. The VACUUM command ignores the retention duration argument except when the value is 0 hours. You cannot set deletedFileRetentionDuration larger than logRetentionDuration.

SHOW TABLES DROPPED respects LIMIT clause

SHOW TABLES DROPPED now correctly respects the LIMIT clause.

January 2026

  • Last updated on