System relies on a proprietary storage layer as AWS moves to separate storage and compute to fit mega AI demands
Amazon has re-engineered its serverless OpenSearch database service, separating storage and compute in a move it claims will benefit developers faced with new demand characteristics of agentic AI.
The new serverless system would avoid the problem of users paying for idle compute capacity between demand bursts, the vendor claims.
Speaking to The Register, Tia White, Director of OpenSearch, AWS said: “Collections can shrink all the way to zero when nothing's happening. We have mitigated the cold start problem, so they spin back up in seconds when traffic is needed as agents restart. It auto-scales 20 times faster than before.”
AWS promises a fully managed search and vector engine designed for customers building AI agents, offering up to 60 percent cost savings compared to the cost of OpenSearch Service clusters provisioned for peak capacity.
AWS has integrated OpenSearch Serverless into Vercel, letting developers spin up new search backends directly from the Vercel console without leaving their workflow. The service also powers the OpenSearch Launchpad inside Kiro - AWS's new agentic coding IDE - providing guided, end-to-end architecture planning for search applications. Broader AI development platform support is coming.
White said the most immediate application would be with developer coding agents. “Historically, search has not had to decouple [storage and compute], because the traffic was pretty predictable. Now with agentic workloads, even the most sophisticated technical teams need to use a serverless offering. Agentic, production-allied workloads are only going to continue to proliferate and grow.”
At the turn of the decade, ElasticSearch was the de facto database manager developers used for enterprise search. However, in 2021, Elastic adopted a more restrictive software license in order to restrict cloud service providers from creating a DBaaS based on the free open source software and making money from it. AWS responded by forking the code to create OpenSearch, which is governed by the Linux Foundation, with contributing organizations including Uber and SAP.
MongoDB and MariaDB have trodden a similar path to Elastic, with debate continuing over whether the cloud giants should be able to make money from database services without paying for the core database itself, or whether a more permissive open source development model is the best option.
White said some of the logic in the new OpenSearch serverless offering is available in the open source project, but a custom-built AWS proprietary storage layer is part of the intellectual property and is not fully open source. She could not rule out AWS making the technology open source in the future, as it has done with some IP in the past, but says there are no current plans to do so.
The OpenSearch serverless launch might be good news for people building on AWS, but bad news for Elastic.
Elastic launched its serverless search offering in 2024, promising decoupled storage and compute and auto-scaling. It updated the service in January, claiming 50 percent higher indexing throughput and 37 percent lower search latency using new AWS Graviton instances at no extra cost to users.
According to the DB-Engines ranking — which is based on website mentions, technical discussions, Google search trends, and jobs ads — ElasticSearch continues to place well above OpenSearch. The pair rank at 11th and 31st place respectively, although ElasticSearch’s ranking has fallen steadily over the last few years. ®