You can now use the AlloyDB Columnar Engine as a read-optimized, in-memory cache for HNSW vector indexes. This feature is generally available (GA). It accelerates vector search performance and increases queries per second (QPS) for vector workloads.
For more information, see Accelerate queries with the Columnar Engine.
]]>You can now monitor the status, throughput, and backlog of the audit logging pipeline for your AlloyDB for PostgreSQL instances and nodes using Cloud Monitoring.
For more information, see Monitor audit log pipeline status.
]]>AlloyDB real-time data access to BigQuery (in Preview) now offers limit pushdown and runtime projects:
LIMIT and OFFSET clauses are automatically pushed down to BigQuery, reducing network transfer and improving query response times. For more information, see Access to real-time data in BigQuery overview.Consider using least-privilege security controls to restrict foreign server usage. For more information, see Secure BigQuery data access using the foreign data wrapper.
]]>You can now use the Model Context Protocol (MCP) Toolbox for Databases to access AlloyDB observability features and advanced query insights directly in your IDE.
]]>You can now sync tables from BigQuery into your AlloyDB instance, either as a one-time operation or on a periodic schedule. This feature (in Preview) lets you enable operational analytics that benefit from low-latency, transactional access to your data lake.
For more information, see Sync BigQuery data to AlloyDB.
AlloyDB integration with BigQuery lets you connect your operational and analytical data through real-time data access (lakehouse federation), periodic data synchronization, and one-time table syncs. These features are in Preview.
For more information, see Choose how to access BigQuery data from AlloyDB.
]]>AlloyDB now supports Best Matching 25 (BM25) indexes for full-text search in
Preview.
You can use the pg_textsearch extension to create BM25 indexes and optimize
probabilistic ranking of full-text search. This feature is supported on AlloyDB
instances running PostgreSQL 17 or 18.
For more information, see Create and manage a BM25 index.
]]>IAM group authentication for AlloyDB is available in Preview for new clusters running PostgreSQL 15 and later. This feature simplifies database user management by allowing access management at the group level, where group members inherit database roles and permissions. To use this feature, enable the alloydb.iam_authentication and alloydb.iam_group_authentication database flags.
For more information, see IAM group authentication and Manage IAM authentication.
]]>AlloyDB write endpoints are now available in Preview. Write endpoints simplify database connection management by providing a stable domain name service (DNS) name for your applications, decoupling them from instance IP addresses. During disaster recovery switchovers or failovers, AlloyDB automatically updates the endpoint to point to the new primary instance.
For more information, see Manage database connections with write endpoints.
AlloyDB now supports cross-region failover in Preview. You can optionally enable cross-region failover to automate the recreation of the original primary when a secondary cluster is promoted while maintaining your replication topology without requiring manual cluster deletion or re-creation. Cross-region failover is supported only for topologies with a single primary cluster and a single secondary cluster.
For more information, see About cross-region replication and Work with cross-region replication.
External search with AlloyDB now supports OpenSearch in Preview.
You can use the external_search_fdw extension to connect to an OpenSearch cluster and query its data directly from your database.
Transparent query forwarding is now available in Preview for clusters compatible with PostgreSQL 17 and 18. With this feature, the primary node in a cluster intercepts read-only queries and selectively forwards them to read pool instances while maintaining read-your-writes consistency.
For more information, see Optimize resources and isolate read queries with transparent query forwarding.
]]>External search with AlloyDB now supports Apache Solr in Preview.
You can use the external_search_fdw extension to connect to a Solr cluster and query its data directly from your database.
Hot standby enhances the AlloyDB high availability (HA) architecture to improve failover times and to ensure consistent performance after failover. AlloyDB continuously replicates transactions to the standby node to keep caches warm and to ensure that the node is ready to take over quickly during a failover. This feature is generally available (GA) in PostgreSQL 18 and is automatically enabled for all new instances. For more information, see the AlloyDB high availability overview.
]]>AlloyDB now offers conversational analytics, which lets users query their operational data using natural language. This feature is powered by the Conversational Analytics API, which can help you translate complex human dialog into precise database queries to provide actionable insights. This feature is in Preview. For more information, see Conversational analytics for AlloyDB overview.
]]>Database server compatibility with PostgreSQL version 18 is now generally available (GA):
The following AlloyDB AI features are available in Preview:
You can now use the ai.hybrid_search() function, which fuses results from
each search type into a single list using the Reciprocal Rank Fusion (RRF)
algorithm. For more information, see Run hybrid vector similarity search.
AlloyDB supports the rum extension for complex full-text search
operations. The rum extension extends standard GIN indexes by storing
positional information directly in the index. This enables faster phrase
searches and relevance ranking without needing to access the table data. For
more information, see Create and manage a RUM index.
When no major version is specified, AlloyDB for PostgreSQL now defaults to PostgreSQL major version 17 for new clusters.
]]>AlloyDB lets you monitor node-level metrics in Google Cloud console and Metrics Explorer to provide detailed troubleshooting guidance for read pools and to identify nodes causing performance regressions. For more information, see System insights metrics reference.
]]>AlloyDB now supports the 2 vCPU C4A machine type (c4a-highmem-2-lssd),
which is powered by Google Axion, Google's custom Arm-based processor.
This expansion provides a smaller entry point and more flexibility for
scaling your production workloads using Axion-based instances. For more information,
see Choose an AlloyDB machine type.
AlloyDB enhanced backups are generally available (GA). You can now select the Enhanced tier during cluster creation, manage your project-level backups with tiered tabs, and delete an enhanced backup. For more information, see Manage enhanced backups.
]]>AlloyDB enhanced backups are generally available (GA). You can now select the Enhanced tier during cluster creation, manage your project-level backups with tiered tabs, and delete an enhanced backup. For more information, see Manage enhanced backups.
]]>The following AlloyDB AI features are now generally available (GA):
Auto vector embeddings provide a scalable, automated solution for managing the lifecycle of vector embeddings for large-scale datasets, eliminating the need for manual reindexing or custom scripts. This feature keeps embeddings in sync with transactional data and now supports incremental refresh in manual mode, ensuring that embeddings are only generated for new or updated rows. Additionally, you can perform incremental table refreshes or migration up to 130x faster than traditional row-by-row processing using bulk mode, improving efficiency for semantic search and Retrieval Augmented Generation (RAG).
AI functions integrate LLMs like Gemini to bring 'world knowledge' to your AlloyDB data and incorporate advanced semantic search and ranking capabilities directly into your SQL workflows. This feature includes out-of-the-box functions for filtering (ai.if), semantic ranking (ai.rank), generation (ai.generate), and forecasting (ai.forecast).
Experience higher performance in AlloyDB AI by utilizing array-based AI functions. You can perform batch processing of natural language prompts directly within your SQL queries, significantly improving efficiency for large-scale AI operations. For more information, see Perform intelligent SQL queries using AI functions.
Gemini Cloud Assist investigation capabilities are now supported in AlloyDB (Preview).
For more information, see Troubleshoot slow queries with AI assistance.
]]>AlloyDB now integrates with Database Center to provide prioritized health monitoring in the Google Cloud console. This integration highlights critical and high-priority risks, offering one-click navigation to recommended fixes and system insights for quick resolution. For more information, see Monitor the health of your AlloyDB clusters and instances.
]]>AlloyDB performance snapshot and reports now support read pool instance nodes, providing deeper observability into read operations and replica-specific performance issues.
New best practices are available for securing generative AI agents using Model Context Protocol (MCP) with Google Cloud databases. This guide covers key security measures like least privilege, native database controls, and secure agent design to help you build safer AI applications. For more information, see Best practices for securing agent interactions with Model Context Protocol.
You can now make AI function calls in bulk rather than row-by-row, which lets you scale your intelligent workflows faster with new support for array-based processing. For more information, see Perform intelligent SQL queries using AI functions.
This feature is in Preview.
You can now use the AlloyDB remote MCP server. The AlloyDB remote MCP server lets you interact easily with AlloyDB clusters from LLMs, AI applications, and AI-enabled development platforms.
This feature is in Preview.
]]>We are announcing the release of support for the AlloyDB language connectors and Auth Proxy with Auto IAM Authentication and managed connection pooling. This feature and the fix for the issue from below is available starting with maintenance version 20260107.02_05. Clusters with a maintenance window that may not have received this release can use self-service maintenance to perform a maintenance update.
]]>Virtual columns for expressions is a feature of the columnar engine in Preview that significantly improves query performance and reduces CPU consumption. It caches the results of frequently used expressions, which is especially beneficial for analytical workloads on large datasets. This feature is supported for PostgreSQL version 16 and higher.
]]>Database server compatibility with PostgreSQL version 18 is now available for preview (Preview). You can create AlloyDB clusters with PostgreSQL 18 compatibility.
]]>Automatic IAM authentication is unavailable when you use managed connection pooling with the AlloyDB Auth Proxy and Language Connectors. To sign into your database without a password, use manual IAM authentication. For more information, see Connect using an IAM account
]]>You can
create AlloyDB cluster instances
in Bangkok, Thailand (asia-southeast3). For more information, see
AlloyDB locations and
AlloyDB for PostgreSQL pricing.
AlloyDB now supports the Z3 machine series, which are powered by 4th generation Intel x86 processors (Sapphire Rapids) with Titanium SSD. These instances offer machine sizes, with up to 88 vCPU and 704 GiB RAM, that let you run storage-intensive workloads with large working datasets. For more information, see Choose an AlloyDB machine type. This feature is generally available (GA).
]]>Memory usage estimation is more accurate for high-dimensional vector indexes. This
fix prevents out of memory (OOM) errors by enforcing defined memory constraints
throughout the index build process. You might need to increase your
maintenance_work_mem settings to align with the real usage estimates.
The extension vector, which includes pgvector functions and operators, is updated to version 0.8.1.
Managed connection pooling is now generally available (GA). This feature optimizes resource usage to improve workload scalability and reliability. It is compatible with the AlloyDB Auth Proxy and Language Connectors. For more information, see Configure managed connection pooling.
AlloyDB database performance snapshot reports now include a SQL Report section, which lists the top 50 queries by total elapsed time, read I/O, and standard deviation of elapsed time. This helps you identify and optimize resource-intensive queries.
]]>You can build data agents that interact with the data in your database using conversational language. Use these data agents as tools to empower your applications. For more information, see Data agents overview. This feature is available in Preview, and access to it requires a sign-up.
You can now use Gemini 3.0 Flash
(Preview)
when you call generative AI functions in AlloyDB, such as AI.GENERATE. Use the
model name gemini-3-flash-preview. For more information, see
Use Gemini 3.0 models.