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Ten years in the past, we introduced the final availability of Amazon Aurora, a database that mixed the pace and availability of high-end business databases with the simplicity and cost-effectiveness of open supply databases.
As Jeff described it in its launch weblog submit: “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 creating Aurora over a decade in the past, we made a basic architectural choice that may change the database panorama perpetually: we decoupled storage from compute. This novel method enabled Aurora to ship the efficiency and availability of business databases at one-tenth the associated fee.
This is likely one of the the reason why lots of of 1000’s of AWS prospects select Aurora as their relational database.
In the present day, I’m excited to ask you to affix us for a livestream occasion on August 21, 2025, to have fun a decade of Aurora database innovation.
A short look again on the previous
All through the evolution of Aurora, we’ve centered on 4 core innovation themes: safety as our high precedence, scalability to fulfill rising workloads, predictable pricing for higher value administration, and multi-Area capabilities for world functions. Let me stroll you thru some key milestones within the Aurora journey.
We previewed Aurora at re:Invent 2014, and made it typically out there in July 2015. At launch, we offered 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 grew to become typically out there 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 offer predictable pricing with as much as 40 p.c value financial savings for I/O-intensive functions. 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 information from Aurora by eradicating the necessity so that you can construct and keep complicated information pipelines that carry out extract, remodel, and cargo (ETL) operations. This yr we added Aurora MySQL zero-ETL integration with Amazon Sagemaker, enabling close to real-time entry of your information 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 Information Bases and launched Aurora PostgreSQL Limitless Database, a serverless horizontal scaling (sharding) functionality.
To simplify scaling for purchasers, we additionally elevated the utmost storage to 128 TiB in September 2020, permitting many functions 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 value effectivity.
Most lately, at re:Invent 2024, we introduced Amazon Aurora DSQL, which grew to become typically out there in Could 2025. Aurora DSQL represents our newest innovation in distributed SQL databases, providing active-active excessive availability and multi-Area sturdy consistency. It’s the quickest serverless distributed SQL database for at all times out there functions, effortlessly scaling to fulfill any workload demand with zero infrastructure administration.
Aurora DSQL builds on our unique architectural rules of separation of storage and compute, taking them additional with unbiased scaling of reads, writes, compute, and storage. It gives 99.99% single-Area and 99.999% multi-Area availability, with sturdy 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 information sources and providers.
Let’s have fun 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 resolve on behalf of shoppers.
The occasion additionally presents sensible demonstrations that present you the right way to implement key options. You’ll see the right way to construct AI-powered functions utilizing pgvector, perceive value optimization with the brand new Aurora DSQL pricing mannequin, and learn to obtain multi-Area sturdy consistency for world functions.
The interactive format contains Q&A alternatives with Aurora specialists, so that you’ll have the ability to get your particular technical questions answered. It’s also possible to obtain AWS credit to check new Aurora capabilities.
For those who’re focused on agentic AI, you’ll notably profit from the classes on MCP servers, Strands Brokers, and the right way to combine Strands Brokers with Aurora DSQL, which exhibit the right way 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 functions, these classes will assist you to perceive the right way to use the most recent Aurora options.
Register in the present day to safe your spot and be a part of this celebration of database innovation.
To the following decade of Aurora innovation!
