Release notes for Aurora DSQL

🐘 PostgreSQL Compatibility — JSONB data type with compression — Aurora DSQL now supports the PostgreSQL JSONB data type, with optional compression for stored data. You can use JSONB columns to store semi-structured data such as system configuration metadata, API parameters, and event logs alongside relational data, and existing code and tools that depend on PostgreSQL's JSONB type work with Aurora DSQL without modification. Aurora DSQL enables PostgreSQL compression by default, storing larger JSONB payloads more efficiently. For more information, see Supported data types in Aurora DSQL.

🆕 Feature — Change data capture (Preview) — Aurora DSQL introduces support for change data capture (CDC) in preview, enabling you to stream real-time database changes directly to Amazon Kinesis Data Streams. This fully managed capability removes the need to build or maintain custom streaming pipelines, making it easier to build event-driven applications, power real-time analytics pipelines, and synchronize data across systems. For more information, see Getting started with CDC.

🌍 Region Expansion — Aurora DSQL available in five additional Regions — Single-Region clusters are now available in Asia Pacific (Hong Kong), Asia Pacific (Mumbai), Asia Pacific (Singapore), Europe (Stockholm), and South America (São Paulo). For a complete list of supported Regions, see Region availability for Aurora DSQL.

🐘 PostgreSQL Compatibility — JSON data type with compression — Aurora DSQL now supports the PostgreSQL JSON data type with optional compression. You can store semi-structured data such as API payloads, configuration objects, or event logs alongside relational data. Aurora DSQL enables PostgreSQL compression by default, storing larger JSON payloads more efficiently.

🐘 PostgreSQL Compatibility — ALTER DEFAULT PRIVILEGES support — Aurora DSQL now supports PostgreSQL's ALTER DEFAULT PRIVILEGES for tables, sequences, functions, and types. Newly created objects automatically inherit configured default privileges, removing the need for manual GRANT statements after each object creation.

🐘 PostgreSQL Compatibility — CREATE SCHEMA with nested statements — Aurora DSQL now supports nested CREATE SEQUENCE and GRANT statements within a CREATE SCHEMA command, enabling developers to define schema objects and their permissions in a single atomic operation.

🐘 PostgreSQL Compatibility — ALTER USER/ROLE RENAME support — Aurora DSQL now supports ALTER USER/ROLE/GROUP ... RENAME TO, enabling administrators to rename database roles without dropping and recreating them. The rename propagates across all active sessions through catalog version notifications.

🐘 PostgreSQL Compatibility — ALTER ROUTINE support — Aurora DSQL now supports ALTER ROUTINE ... SET SCHEMA, SET OWNER, and RENAME TO, along with GRANT, REVOKE, COMMENT ON, and DROP ROUTINE. The ROUTINE keyword is a PostgreSQL umbrella term covering both functions and procedures, enabling object-relational mapping (ORM) and migration tools that emit ROUTINE syntax to work without modification.

🆕 Feature — AWS Backup adds Aurora DSQL support for AWS Organizations backup policies — AWS Backup now supports Aurora DSQL clusters as a resource type in AWS Organizations backup policies. Organization administrators can define backup policy rules that directly target Aurora DSQL clusters across member accounts, providing more precise control over which resources are included in Organization-wide backup plans.

🔌 Developer Tools — Aurora DSQL Connector for PHP (PDO_PGSQL) — Added the Aurora DSQL Connector for PHP that handles IAM token generation, Secure Sockets Layer (SSL) configuration, and connection pooling for PHP applications. The connector provides opt-in optimistic concurrency control (OCC) retry with exponential backoff. For more information, see Connecting to Aurora DSQL clusters with a PHP connector.

🔌 Developer Tools — Aurora DSQL Connectors for .NET (Npgsql) and Rust (SQLx) — Added connectors for .NET and Rust that handle IAM token generation, SSL configuration, and connection pooling. Both connectors provide opt-in OCC retry with exponential backoff, custom IAM credential providers, and AWS profile support. For more information, see Aurora DSQL connectors.

⚡ Performance — Faster INSERT ON CONFLICT statements — Aurora DSQL improves write performance for INSERT ON CONFLICT statements. The improvement scales with the number of rows proposed for insertion per transaction, so workloads that batch many INSERT ON CONFLICT statements into a single transaction see the largest gains.

⚡ Performance — Faster uniqueness validation for large insert workloads — Aurora DSQL now validates secondary unique-index constraints in batches rather than one key at a time, accelerating large insert and migration workloads. The speedup is most pronounced for transactions that touch many rows or tables with multiple unique secondary indexes — workloads where uniqueness validation was previously the bottleneck. For example, inserting 1,000 rows into a table with one unique secondary index now completes in 577 ms, down from 1,041 ms (1.8x faster).

🔌 Developer Tools — Aurora DSQL Connector for Ruby (pg gem) — Added the Aurora DSQL Connector for Ruby that handles IAM token generation, SSL configuration, and connection pooling. The connector provides opt-in OCC retry with exponential backoff and custom IAM credential providers. For more information, see Connecting to Aurora DSQL clusters with a Ruby pg connector.

🔌 Developer Tools — Integrations for Visual Studio Code SQLTools and DBeaver — Added the Aurora DSQL Driver for SQLTools and the Aurora DSQL Plugin for DBeaver Community Edition. Both integrations simplify database connectivity by automatically handling IAM authentication and transparently managing access tokens. The SQLTools driver is also available on Open VSX Registry for use with VS Code-compatible editors such as Cursor and Kiro.

🆕 Feature — Aurora DSQL Playground — AWS launches a browser-based playground that enables developers to interact with an Aurora DSQL database without requiring an AWS account. With zero setup or infrastructure configuration, developers can create schemas, load data, and execute SQL queries directly from their browser with built-in sample datasets. To start exploring, visit the Aurora DSQL Playground.

🔌 Developer Tools — Support for Tortoise, Flyway, and Prisma — Added integrations for popular ORM and database migration tools: an adapter for Tortoise (Python ORM), a dialect for Flyway (schema management tool), and CLI tools for Prisma (Node.js ORM). These integrations handle IAM authentication and Aurora DSQL-specific compatibility requirements automatically.

🔌 Developer Tools — Go, Python, and Node.js connectors with WebSocket support — Added Aurora DSQL Connectors for Go (pgx), Python (asyncpg), and Node.js (WebSocket for Postgres.js) that simplify IAM authentication. Each connector automatically generates tokens for each connection. The Postgres.js connector additionally supports WebSocket protocol for environments where Transmission Control Protocol (TCP) connections aren't available. For more information, see Aurora DSQL connectors.

✨ AI Integration — Aurora DSQL integrates with Kiro powers and AI agent skills — Aurora DSQL integration with Kiro powers and AI agent skills enables developers to build Aurora DSQL-backed applications faster with AI-assisted development. The Kiro power bundles the Aurora DSQL Model Context Protocol (MCP) server with development best practices for one-click installation. The Aurora DSQL skill extends the same capabilities to additional AI coding agents through the Skills CLI. For more information, see Aurora DSQL Steering: Skills and Powers.

🐘 PostgreSQL Compatibility — Identity columns and sequence objects — Aurora DSQL now supports identity columns and sequence objects, enabling developers to generate auto-incrementing, integer-based IDs directly in the database using familiar SQL patterns. For more information, see Sequences and identity columns.

🌍 Region Expansion — Aurora DSQL available in Canada and Australia Regions — Aurora DSQL is now available with single-Region clusters in Asia Pacific (Melbourne), Asia Pacific (Sydney), Canada (Central), and Canada West (Calgary). For a complete list of supported Regions, see Region availability for Aurora DSQL.

🔌 Developer Tools — Aurora DSQL Connector for Go — Added the Aurora DSQL Connector for Go, which wraps pgx with automatic IAM authentication for token generation, SSL configuration, and connection management. For more information, see Connecting to Aurora DSQL clusters with a Go connector.

🐘 PostgreSQL Compatibility — Index support for the NUMERIC data type — Aurora DSQL now supports indexes on the NUMERIC data type, allowing customers to use NUMERIC columns as primary keys and in secondary indexes for improved query performance on decimal and financial data.

🔗 Integration — Aurora DSQL available in v0 by Vercel — AWS databases including Aurora DSQL are now available in v0 by Vercel, enabling developers to quickly spin up and connect to Aurora DSQL databases directly from the Vercel platform.

✨ AI Integration — AWS Labs Aurora DSQL MCP Server updates — Updated MCP Server with installation approaches for Claude Code and Codex, including CLI-based setup. For more information, see AWS Labs Aurora DSQL MCP Server.

🔗 Integration — Aurora DSQL available in the Vercel Marketplace — AWS databases including Aurora DSQL are now available on the Vercel Marketplace, allowing developers to provision Aurora DSQL clusters in seconds directly from Vercel's developer platform.

🆕 Feature — Fast cluster creation — Aurora DSQL now supports cluster creation in seconds, enabling developers to instantly provision Aurora DSQL databases to rapidly prototype new ideas and leverage the integrated query editor in the AWS Management Console to immediately start building.

🆕 Feature — AWS PrivateLink with Direct Connect support — Added private Domain Name System (DNS) setup and the cluster ID connection option for AWS PrivateLink with Direct Connect or Amazon VPC peering. For more information, see Managing and connecting to Aurora DSQL clusters using AWS PrivateLink.

🔌 Developer Tools — Python, Node.js, and JDBC Connectors — Aurora DSQL launches new Python, Node.js, and Java Database Connectivity (JDBC) connectors that simplify IAM authorization, enabling developers to connect to Aurora DSQL clusters using standard PostgreSQL drivers with automatic IAM token management. For more information, see Aurora DSQL connectors.

🆕 Feature — Storage volume increased to 256 TiB — Aurora DSQL database clusters now support up to 256 terabytes of storage volume, doubling the previous 128 terabyte limit and allowing customers to store and manage larger databases within a single database cluster.

🆕 Feature — Integrated Query Editor in AWS Management Console — Aurora DSQL now provides an integrated query editor for browser-based SQL access in the AWS Management Console. Customers can securely connect to their Aurora DSQL clusters and run SQL queries directly from the console without installing or configuring external clients. For more information, see Getting started with the Aurora DSQL Query Editor.

🆕 Feature — Statement-level cost estimates in query plans — Aurora DSQL now provides statement-level cost estimates and query plans, surfacing per-category breakdowns including compute, read, write, and multi-Region costs with total estimated DPUs to help developers immediately get visibility into their estimated cost profile. For more information, see Working with Aurora DSQL explain plans.

🔗 Integration — Using JupyterLab with Aurora DSQL — Published a step-by-step guide for connecting Aurora DSQL with JupyterLab for both local and Amazon SageMaker AI environments. For more information, see Using JupyterLab with Aurora DSQL.

🆕 Feature — FIPS 140-3 compliant endpoints — Aurora DSQL now supports Federal Information Processing Standards (FIPS) 140-3 compliant endpoints, enabling customers in regulated industries and government sectors to meet federal security requirements when connecting to Aurora DSQL clusters.

🆕 Feature — Resource-based policy support — Aurora DSQL now supports resource-based policies, allowing customers to attach inline policies directly to Aurora DSQL clusters for fine-grained access control with new permissions: PutClusterPolicy, GetClusterPolicy, and DeleteClusterPolicy. For more information, see Resource-based policies for Aurora DSQL.

🌍 Region Expansion — Aurora DSQL available in Europe (Frankfurt) — Aurora DSQL is now available in the Europe (Frankfurt) Region, expanding availability for European customers who need to deploy distributed SQL databases with data residency in the European Union (EU).

🆕 Feature — AWS Fault Injection Service integration — Aurora DSQL now integrates with AWS Fault Injection Service (AWS FIS), allowing customers to inject failures into single-Region and multi-Region Aurora DSQL clusters to test fault tolerance and validate application error handling and recovery mechanisms.

🆕 Feature — AWS Backup improves Aurora DSQL multi-Region restore workflow — AWS Backup improves the Aurora DSQL multi-Region restore workflow, simplifying the process of restoring Aurora DSQL backups across AWS Regions for disaster recovery and data migration scenarios. For more information, see Backup and restore for Aurora DSQL.

🌍 Region Expansion — Aurora DSQL available in Asia Pacific (Seoul) — Aurora DSQL is now available in the Asia Pacific (Seoul) Region, expanding availability for customers in South Korea and the broader Asia Pacific region.

🚀 Major Release — General availability of Aurora DSQL — Aurora DSQL is now generally available (GA). Aurora DSQL is a serverless, distributed SQL database with PostgreSQL compatibility, active-active high availability, and virtually unlimited scale. The GA release includes CloudWatch monitoring, AWS Backup integration, and data encryption with customer-managed KMS keys. For more information, see What is Aurora DSQL?

🆕 Feature — AWS PrivateLink for Aurora DSQL — Aurora DSQL now supports AWS PrivateLink, enabling customers to simplify private network connectivity between virtual private clouds (VPCs), Aurora DSQL, and on-premises data centers using interface Amazon VPC endpoints and private IP addresses. For more information, see Managing and connecting to Aurora DSQL clusters using AWS PrivateLink.

🚀 Major Release — Public preview launch of Aurora DSQL — Aurora DSQL launches in public preview as a new serverless distributed SQL database. Aurora DSQL offers virtually unlimited scale, PostgreSQL v16 compatibility, multi-Region active-active support with a 99.999% availability service level agreement (SLA), IAM authentication, and optimistic concurrency control. For more information, see What is Aurora DSQL?