AWS positioned highest in execution in the 2023 Gartner Magic Quadrant for Cloud Database Management Systems

AWS has been named a Leader for the ninth consecutive year in the 2023 Gartner Magic Quadrant for Cloud Database Management Systems, and we have been positioned highest for ability to execute. We are honored to be recognized for delivering value for customers in a year where the possibilities of generative AI have captured all of our imaginations. We are even more excited about the vision that we will deliver for customers so they can effortlessly extract the most value from their data to power their businesses.

This recognition is even more special as we reflect upon our interactions with tens of thousands of customers and partners at AWS re:Invent 2023. The pure excitement expressed about our announcements created an exhilarating level of energy among our builder community—all of whom are committed to solving the challenges of today and tomorrow in the data management world. In this post, we share some of the generally available launches already receiving tremendous traction among customers.

Amazon ElastiCache Serverless

Caches are a straightforward way to improve price-performance of any read- or compute-heavy workload. But many customers are also quite familiar with the expertise required to properly configure a cache and manage capacity for fluctuating workloads. During Peter DeSantis’ keynote, the delightful howls reacting to the general availability of Amazon ElastiCache Serverless underscores the value of this new feature—saving you time and money with no expertise required!

Amazon RDS for Db2

As of this writing, 76 of the top Fortune 100 companies use IBM Db2 databases. We were thrilled to have Minaz Merali, VP of Product Management at IBM, join us in announcing the general availability of Amazon RDS for Db2, providing Db2 customers another option to remove undifferentiated database management tasks while achieving high availability and cloud agility. Db2 databases are also highly compatible with Oracle databases, which make them a great solution for Oracle customers who are seeking to consolidate workloads on a single database engine. Moreover, IBM software as a service (SaaS) applications will be powered by Amazon RDS for Db2. This is just the beginning of our partnership in delivering exceptional value to customers.

Vector search now available in your database of choice

We have always believed in giving our customers choice, because each use case is unique. And across the many conversations in 2023, our customers said they wanted to perform vector search using their existing database of choice for their application. This is why, earlier in 2023, we announced the full suite of vector database capabilities, including vector search, in Amazon OpenSearch Service, Amazon Aurora, and Amazon Relational Database Service (Amazon RDS). Based on customer feedback, we knew we had to do more.

At re:Invent, we announced the general availability of vector engines for Amazon OpenSearch Serverless, and vector search for Amazon DocumentDB (with MongoDB compatibility) and Amazon Neptune. In addition, Amazon DynamoDB customers can perform near-real-time vector search using the zero-ETL integration with OpenSearch Service. We also showcased how the database performance for vector search is rapidly evolving. As an example, in the past few months, the innovation on Aurora Optimized Reads in combination with pgvector delivered a 20-fold improvement in throughput with single-digit millisecond response times. Our continued investments will lead to rapid advancements to deliver new performance standards on throughput and recall with the single-digit milliseconds response times—all optimized for price. We are also focused on automating the Retrieval Augmented Generation (RAG) workflow with the general availability of Aurora support for knowledge bases for Amazon Bedrock. And we are just getting started, with additional database integrations with Amazon Bedrock coming soon!

Zero-ETL integrations across analytics and search use cases

KINTO Technologies, a subsidiary of Toyota focused on mobility services like car sharing, needed the ability to perform near-real-time analytics to approve customer contracts. To do this, they needed to replicate data from their multiple business units, and then transform the data into a standard schema. Only then could KINTO analyze the data to make decisions. As their transactions grew, so did the processing time. With Aurora zero-ETL integration with Amazon Redshift, KINTO stored application data in Aurora and used Amazon Redshift to analyze it without having to invest resources to move the data. As a result, they can approve contracts in a minute—10 times faster than before. Additionally, KINTO estimates they saved 5 months in engineering time that would have previously been spent building and managing pipelines. Stories like KINTO’s inspired AWS to expand zero-ETL integrations so customers can analyze data stored on their favorite operational databases without having to design, build, and manage complex data pipelines. And many of our customers told us that they also wanted this for search use cases, which is why we started with the general availability of DynamoDB zero-ETL integration with OpenSearch Service—the first of many to come!

Also, in preview, we encourage you to try Amazon Aurora Limitless Database and AI-driven scaling and optimizations for Amazon Redshift Serverless.

Generative AI powering our data services

Customers work with data in many ways. As part of our vision, we are applying generative AI across our services to transform customers’ experiences with data. In preview, Amazon Q is a generative AI-powered assistant available in Amazon QuickSight for enhancing the productivity of business users with generative business intelligence (BI) capabilities. Amazon Q is also in preview for Amazon Redshift, enabling customers to author SQL queries using natural language. We also announced the preview of AI recommendations in Amazon DataZone, a generative AI-based capability to create comprehensive and contextualized business descriptions that improves data discovery, data understanding, and data usage. To improve developer productivity, Amazon CodeWhisperer—an AI coding companion—is now generally available in AWS Glue Studio notebooks and Amazon EMR Studio. Finally, we released OpenSearch Assistant, a toolkit designed to provide OpenSearch developers with flexible and customizable tools for building generative AI experiences.

Building together

At AWS, we are eager to hear how customers are using these new capabilities. We remain committed to inventing solutions to help our customers unlock value from their data to grow their businesses. We thank every customer for spending time to interact with us and learn about our latest innovations at 2023 re:Invent—and we know this Gartner recognition is because of our customers. The journey to the cloud and cloud-native databases is just the beginning, and we are here to help our customers wherever they are in their journey.

Access the complete 2023 Gartner Magic Quadrant for Cloud Database Management Systems report to learn more.

Gartner, Magic Quadrant for Cloud Database Management Systems, Adam Ronthal, Rick Greenwald, Xingyu Gu, Ramke Ramakrishnan, Aaron Rosenbaum, and Henry Cook, December 18, 2023. Gartner and Magic Quadrant are registered trademarks of Gartner, Inc. and/or its affiliates in the US and internationally and are used herein with permission. All rights reserved. The report was previously named Magic Quadrant for Operational Database Management Systems from 2014–2019. This graphic was published by Gartner, Inc., as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from AWS. Gartner does not endorse any vendor, product, or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. Gartner and Magic Quadrant are registered trademarks of Gartner, Inc. and/or its affiliates in the US and internationally and are used herein with permission. All rights reserved.

About the authors

Rahul Pathak is Vice President, Databases, encompassing Amazon Aurora, Amazon Redshift, and Amazon QLDB.

Jeff Carter is the Vice President, Databases & Migrations, encompassing Amazon Relational Database Services (Amazon RDS), Amazon ElastiCache, Amazon DocumentDB (with MongoDB compatibility), Amazon MemoryDB for Redis, Amazon Neptune, Amazon Timestream, AWS Database Migration Service, and the Data Migration Accelerator program.

G2 Krishnamoorthy is the Vice President, Analytics, encompassing Amazon DataZone, AWS Glue, Amazon Athena, Amazon OpenSearch Service, Amazon QuickSight, and Amazon EMR.

Colin Lazier is Vice President and General Manager of Amazon DynamoDB and Amazon Keyspaces (for Apache Cassandra).