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Ten years in the past, we introduced the final availability of Amazon Aurora, a database that mixed the velocity and availability of high-end industrial databases with the simplicity and cost-effectiveness of open supply databases.
As Jeff described it in its launch weblog publish: “With storage replicated each inside and throughout three Availability Zones, together with an replace mannequin pushed by quorum writes, Amazon Aurora is designed to ship excessive efficiency and 99.99% availability whereas simply and effectively scaling to as much as 64 TiB of storage.”
After we began growing Aurora over a decade in the past, we made a basic architectural determination that will change the database panorama eternally: we decoupled storage from compute. This novel strategy enabled Aurora to ship the efficiency and availability of economic databases at one-tenth the price.
This is among the the explanation why tons of of hundreds of AWS prospects select Aurora as their relational database.
At this time, I’m excited to ask you to hitch us for a livestream occasion on August 21, 2025, to have a good time a decade of Aurora database innovation.
A quick look again on the previous
All through the evolution of Aurora, we’ve targeted on 4 core innovation themes: safety as our prime precedence, scalability to fulfill rising workloads, predictable pricing for higher price administration, and multi-Area capabilities for international purposes. Let me stroll you thru some key milestones within the Aurora journey.
We previewed Aurora at re:Invent 2014, and made it typically accessible in July 2015. At launch, we introduced Aurora as “a brand new cost-effective MySQL-compatible database engine.”
In June 2016, we launched reader endpoints and cross-Area learn replicas, adopted by AWS Lambda integration and the power to load tables straight from Amazon S3 in October. We added database cloning and export to Amazon S3 capabilities in June 2017 and full compatibility with PostgreSQL in October that yr.
The journey continued with the serverless preview in November 2017, which turned typically accessible in August 2018. International Database launched in November 2018 for cross-Area catastrophe restoration. We launched blue/inexperienced deployments to simplify database updates, and optimized learn cases to enhance question efficiency.
In 2023, we added vector capabilities with pgvector for similarity search for Aurora PostgreSQL, and Aurora I/O-Optimized to supply predictable pricing with as much as 40 % price financial savings for I/O-intensive purposes. We launched Aurora zero-ETL integration with Amazon Redshift which permits close to real-time analytics and ML utilizing Amazon Redshift on petabytes of transactional knowledge from Aurora by eradicating the necessity so that you can construct and keep complicated knowledge pipelines that carry out extract, rework, and cargo (ETL) operations. This yr we added Aurora MySQL zero-ETL integration with Amazon Sagemaker, enabling close to real-time entry of your knowledge within the lakehouse structure of SageMaker to run a broad vary of analytics.
In 2024, we made it as easy as only one click on to pick out Aurora PostgreSQL as a vector retailer for Amazon Bedrock Data Bases and launched Aurora PostgreSQL Limitless Database, a serverless horizontal scaling (sharding) functionality.
To simplify scaling for patrons, we additionally elevated the utmost storage to 128 TiB in September 2020, permitting many purposes to function inside a single occasion. Final month, we’ve additional simplified scaling by doubling the utmost storage to 256 TiB, with no upfront provisioning required and pay-as-you-go pricing primarily based on precise storage used. This allows much more prospects to run their rising workloads with out the complexity of managing a number of cases whereas sustaining price effectivity.
Most not too long ago, at re:Invent 2024, we introduced Amazon Aurora DSQL, which turned typically accessible in Might 2025. Aurora DSQL represents our newest innovation in distributed SQL databases, providing active-active excessive availability and multi-Area robust consistency. It’s the quickest serverless distributed SQL database for all the time accessible purposes, effortlessly scaling to fulfill any workload demand with zero infrastructure administration.
Aurora DSQL builds on our unique architectural ideas of separation of storage and compute, taking them additional with unbiased scaling of reads, writes, compute, and storage. It supplies 99.99% single-Area and 99.999% multi-Area availability, with robust consistency throughout all Regional endpoints.
And in June, we launched Mannequin Context Protocol (MCP) servers for Aurora, so you’ll be able to combine your AI brokers along with your knowledge sources and providers.
Let’s have a good time 10 years of innovation
By attending the August 21 livestream occasion, you’ll hear from Aurora technical leaders and founders, together with Swami Sivasubramanian, Ganapathy (G2) Krishnamoorthy, Yan Leshinsky, Grant McAlister, and Raman Mittal. You’ll study straight from the architects who pioneered the separation of compute and storage in cloud databases, with technical insights into Aurora structure and scaling capabilities. You’ll additionally get a glimpse into the way forward for database expertise as Aurora engineers share their imaginative and prescient and talk about the complicated challenges they’re working to unravel on behalf of shoppers.
The occasion additionally provides sensible demonstrations that present you find out how to implement key options. You’ll see find out how to construct AI-powered purposes utilizing pgvector, perceive price optimization with the brand new Aurora DSQL pricing mannequin, and discover ways to obtain multi-Area robust consistency for international purposes.
The interactive format consists of Q&A alternatives with Aurora specialists, so that you’ll be capable of get your particular technical questions answered. You can too obtain AWS credit to check new Aurora capabilities.
In the event you’re enthusiastic about agentic AI, you’ll significantly profit from the classes on MCP servers, Strands Brokers, and find out how to combine Strands Brokers with Aurora DSQL, which display find out how to safely combine AI capabilities along with your Aurora databases whereas sustaining management over database entry.
Whether or not you’re operating mission-critical workloads or constructing new purposes, these classes will make it easier to perceive find out how to use the newest Aurora options.
Register immediately to safe your spot and be a part of this celebration of database innovation.
To the subsequent decade of Aurora innovation!