Neo4j Aura Database – December - Graph Database & Analytics

Release Date: 16 December 2025

The Neo4j Aura December release has started to roll out, commencing on AuraDB Free and progressing to higher tiers later.

Release Note for Neo4j 2025.11.0 (Release date: 16 December 2025)

Adds new collection-based functions: coll.distinct, coll.flatten, coll.indexOf, coll.insert, coll.max, coll.min, coll.remove, coll.sort. See documentation.

MATCH and MERGE queries that use dynamic labels, like MATCH (p:$(“Person”) { id: 123 }) can now be much faster, since they make use of property indexes. Please see the Cypher Manual documentation for dynamic MATCH, and dynamic MERGE.
Add a new planner operator MergeUniqueNode, speeding up some merge queries when there are uniqueness constraints. For documentation, see here.
Add a new planner operator MergeInto, speeding up queries like MATCH (a), (b) MERGE (a)-[r:R]->(b). See documentation.

Previously, users could set a property to its existing value without triggering a database change or transaction log entry, and this action was permitted even if they lacked the necessary permission to set the property. Now, any attempt to set a property, even if the value remains the same, will be recorded as a change in the database and the transaction log. Consequently, permissions are now consistently enforced: users who are not allowed to set a property will always be blocked from attempting to set it, regardless of whether the property value is actually modified. This resolves CVE-2025-12738
Replaces error 42N68 with the correct 42I58 error code.
Fixes bug where IF NOT EXISTS for fulltext indexes would mistakenly also match on other indexes on the same schema and not just fulltext indexes:
Fixes bug where ANY INDEX instead of ANY FULLTEXT INDEX on the same label/reltype and property combination caused the IF NOT EXISTS for fulltext indexes to be triggered, and no index to be created

Added new GenAI function ai.text.embed and procedure ai.text.embedBatch to generate vector embeddings as Neo4j vector types. These functions and procedures are available for OpenAI, Azure OpenAI, Google VertexAI and Amazon Bedrock. See documentation for more details.
Added a new function ai.text.completion to generate text based on a textual input prompt. This function is available for Azure OpenAI, OpenAI, Google VertexAI and Amazon Bedrock. See documentation for more details.
Added two new procedures: ai.text.embed.providers and ai.text.completion.providers, which list the allowed providers and their config requirements.

Fix for error: “java.lang.ArrayIndexOutOfBoundsException: Index 2 out of bounds for length 2” which occurred on rare occasions when extremely long (2000+ characters) Label, Type, or property name values were used.

Please refer to the changelog for full details of the changes, and Neo4j Release notes for all changes to other Neo4j products and services.

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