As part of Bigtable Enterprise Plus edition, you can configure a retention period of up to 365 days for backups. This feature is generally available (GA). For more information, see Bigtable backups overview.
]]>You can enable row-affinity routing for a standard app profile in the Google Cloud console. For more information, see Create a standard app profile.
]]>You can use Aerospike migration tools to migrate data from Aerospike to Bigtable with minimal or zero downtime. This feature is available in Preview. For more information, see Migrate Aerospike to Bigtable.
]]>You can use Bigtable agent skills to let AI agents assist with Bigtable-related tasks, such as schema design, generating SQL queries, and infrastructure management.
]]>You can use window functions with GoogleSQL in Bigtable to perform advanced analytic operations over multiple table rows. This feature is generally available (GA). For more information, see Window functions.
]]>The Bigtable editions feature is generally available (GA). Bigtable editions introduces advanced features in performance, analytic query capability, and resource management. You can choose between the Enterprise and Enterprise Plus edition to select the right capabilities for your workloads. For more information, see Editions overview.
Bigtable provides an in-memory tier as part of its hybrid storage architecture. This tier provides sub-millisecond read latency and high throughput for time-sensitive data with independent vertical scaling to handle traffic surges. The in-memory tier is available only in the Enterprise Plus edition in Preview. For more information, see In-memory tier overview.
Bigtable tiered storage limit increases from 32 TB to 64 TB per node. This expansion provides higher storage density to support retention of larger volumes of infrequently accessed data and is available only in the Enterprise Plus edition. Tiered storage is available in Preview.
As part of Bigtable editions, you can use Data Boost to read data from tiered storage and HDD clusters. This feature is available only in the Enterprise Plus edition and is generally available (GA).
As part of Bigtable editions, you can use Data Boost to run GoogleSQL queries. This feature is available only in the Enterprise Plus edition and is generally available (GA). For more information, see High-throughput SQL analysis with Data Boost.
As part of Bigtable editions, you can configure which cluster in a replicated instance is used for automated backups. This feature provides greater cost control and backup resource management. This feature is available only in the Enterprise Plus edition and is generally available (GA). For more information, see Bigtable backups overview.
]]>You can use the Database Insights remote MCP server to analyze Bigtable's performance and system metrics. This feature is generally available (GA).
Bigtable continuous materialized views are generally available (GA). These views let you create precomputed tables that Bigtable automatically keeps in sync with your source data for low-latency queries and real-time insights.
Bigtable free trial instances are generally available (GA). These instances let you learn and explore Bigtable features for 90 days at no cost, providing a 1-node SSD cluster and up to 500 GB of storage. For more information, see Free trial instances overview.
The Bigtable remote MCP server is generally available (GA). The Bigtable remote MCP server lets you interact with Bigtable instances from LLMs, AI applications, and AI-enabled development platforms.
]]>You can stream messages from Pub/Sub directly to a Bigtable table using Bigtable subscriptions. This feature lets you write streaming messages to Bigtable without needing a separate subscriber such as Dataflow. This feature is available in Preview.
]]>Dataplex Universal Catalog is now called Knowledge Catalog. The API, client library, CLI, and Identity and Access Management (IAM) names remain unchanged. For more information about how Bigtable metadata interacts with Knowledge Catalog, see Manage data assets using Knowledge Catalog.
]]>You can now use GoogleSQL geography functions to work with geospatial data in Bigtable. This feature is generally available (GA). For more information, see Work with geospatial data and Geography functions reference.
Bigtable supports pipe syntax, an extension to GoogleSQL that lets you build simpler and more concise queries. This feature is generally available (GA).
]]>You can use Gemini in Bigtable Studio to help you write GoogleSQL queries. This feature is available in Preview. For more information, see Write SQL with Gemini assistance.
]]>You can connect to Bigtable from Java applications and other reporting tools that support a generic JDBC adapter by using the Bigtable JDBC driver. This feature is generally available (GA).
You can use protocol buffer (protobuf) schemas to query individual fields within protobuf messages stored as bytes in Bigtable. You can query your protobuf data using GoogleSQL for Bigtable, continuous materialized views, logical views, or BigQuery external tables. This feature is generally available (GA).
]]>You can view the details of Bigtable continuous materialized views in the Google Cloud console.
]]>Bigtable client for Java has modernized its Admin API. For detailed migration steps and code examples, see Upgrading client libraries.
]]>You can manage Bigtable tiered storage configuration in the Google Cloud console and view tiered storage metrics in system insights. For more information, see Create and manage tables.
]]>Bigtable tools in the Agent Development Kit (ADK) are generally available (GA). With these tools, you can build AI agents that interact with Bigtable to discover metadata about Bigtable tables and instances and execute LLM-powered SQL queries.
]]>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 migrate a machine learning feature management workload from Vertex AI Feature Store (Legacy) to a Bigtable instance. For more information, see Migrate from Vertex AI Feature Store (Legacy) to Bigtable.
]]>You can use the Bigtable Admin API MCP server to enable agents and AI applications to perform a range of data-related tasks. This feature is in Preview.
]]>You can use the Flink Bigtable connector version 0.3.2 to connect to Bigtable from Apache Flink version 2.1.0. Additionally, this version of the connector lets you specify the number of mutations to include in each batch sent to Bigtable. This feature is generally available (GA).
]]>Bigtable has a unified, customizable system insights dashboard. This dashboard includes predefined metrics and other Google Cloud metrics. This feature is generally available (GA). For more information, see Customize the system insights dashboard.
]]>Bigtable is available in the asia-southeast3 (Bangkok) region. For more
information, see Bigtable locations.
Continuous materialized views support up to five continuous materialized views per table. This lets you create multiple asynchronous secondary indexes on a table or have a mix of precomputed aggregate views and asynchronous secondary indexes on the same base table. For more information, see Continuous materialized views.
]]>add basic interceptor to client (#1206) (6561cfac)
Add encodings for STRUCT and the Timestamp type (72dfdc44)
add PeerInfo proto in Bigtable API (72dfdc44)
Add Type API updates needed to support structured keys in materialized views (72dfdc44)
support mTLS certificates when available (#1249) (ca20219c)
add PeerInfo proto in Bigtable API (PiperOrigin-RevId: 829585900) (185951b3)
precompute featureflags in client and reuse (#13297) (3b3253ac)
Add experimental Bigtable connection pool with custom load balancing strategy. (#12882) (7aa96127)
Enable ALTS hard bound token in Bigtable w/ direct access (#13153) (90239341)
Enable routing cookie and attempt headers for enhanced retries (#12964) (96cfd47a)
fix project id sent in otel (#13286) (4865868c)
screaming uppercase metric status (#13484) (b35ee8fd)
In the Google Cloud console, you can import data into Bigtable using the Dataflow job builder, a web interface for building and running Dataflow pipelines. This integration provides a pre-populated template to import data from Pub/Sub to Bigtable. You can also create a custom job to import data from other sources. For more information, see Import and export data.
]]>You can use protocol buffer (protobuf) schemas to query individual fields within protobuf messages stored as bytes in Bigtable. First, create and manage your protobuf schemas. Then, query your protobuf data using GoogleSQL for Bigtable or BigQuery external tables. This feature is in Preview.
]]>You can use Cloud KMS Autokey in the Google Cloud console to automate the creation and use of customer-managed encryption keys (CMEK) in Bigtable clusters.
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