|
Ten years in the past, we introduced the final availability of Amazon Aurora, a database that mixed the velocity 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 growing Aurora over a decade in the past, we made a elementary architectural determination that might change the database panorama endlessly: 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 explanation why a whole bunch of 1000’s of AWS clients 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 a good time a decade of Aurora database innovation.
A quick look again on the previous
All through the evolution of Aurora, we’ve centered on 4 core innovation themes: safety as our prime precedence, scalability to satisfy rising workloads, predictable pricing for higher value 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 usually 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 flexibility to load tables immediately 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 12 months.
The journey continued with the serverless preview in November 2017, which grew to become usually 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 p.c value financial savings for I/O-intensive purposes. We launched Aurora zero-ETL integration with Amazon Redshift which allows 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 12 months 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 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 clients to run their rising workloads with out the complexity of managing a number of cases whereas sustaining value effectivity.
Most not too long ago, at re:Invent 2024, we introduced Amazon Aurora DSQL, which grew to become usually accessible 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 accessible purposes, effortlessly scaling to satisfy any workload demand with zero infrastructure administration.
Aurora DSQL builds on our authentic architectural ideas of separation of storage and compute, taking them additional with impartial 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 possibly can combine your AI brokers together with your knowledge sources and companies.
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 immediately 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 know-how 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 provides sensible demonstrations that present you tips on how to implement key options. You’ll see tips on how to construct AI-powered purposes utilizing pgvector, perceive value optimization with the brand new Aurora DSQL pricing mannequin, and learn to obtain multi-Area sturdy consistency for international purposes.
The interactive format consists of Q&A alternatives with Aurora consultants, so that you’ll be capable to get your particular technical questions answered. You too can obtain AWS credit to check new Aurora capabilities.
If you happen to’re desirous about agentic AI, you’ll notably profit from the classes on MCP servers, Strands Brokers, and tips on how to combine Strands Brokers with Aurora DSQL, which display tips on how to safely combine AI capabilities together with your Aurora databases whereas sustaining management over database entry.
Whether or not you’re working mission-critical workloads or constructing new purposes, these classes will enable you to perceive tips on how to use the newest Aurora options.
Register as we speak to safe your spot and be a part of this celebration of database innovation.
To the subsequent decade of Aurora innovation!