Couchbase 8.0 boosts AI scalability with advanced vector search

Couchbase has introduced a major update to its data platform with the launch of Couchbase 8.0, focused on improving how data is organised, indexed, and accessed to enhance the scalability and speed of large-scale artificial intelligence (AI) applications.

Recent research commissioned by Couchbase suggests that a significant number of chief information officers (CIOs) face substantial infrastructure challenges when delivering AI projects. The survey found that 28% of CIOs cite difficulties in managing or accessing necessary data as a key factor disrupting AI projects, and just 16% currently have a vector database capable of efficiently supporting large-scale operations and newer AI use cases.

In response to these issues, Couchbase 8.0 offers multiple vector indexing and retrieval options, enabling rapid searches through billions of data points and catering to a variety of different AI workloads. The company states this is achievable without raising overall infrastructure costs.

Vector search performance

The platform features a range of indexing methods intended to support various demands for speed, recall accuracy, and storage cost. According to independent benchmark testing commissioned by Couchbase, its tunable Hyperscale Vector Indexing (HVI) delivered up to 19,057 queries per second (QPS) with 28-millisecond latency at 66% recall accuracy. In comparison, the identified challenger, listed as a leader in the Gartner Magic Quadrant for Cloud Database Management Systems, achieved 6 QPS with 57% recall accuracy. When optimised for recall accuracy, HVI achieved more than 700 QPS and 93% recall with response times under a second.

Couchbase is positioning the benchmark results as a demonstration of both speed and scalability for enterprise deployments, and the benchmarks indicate that, when tuned for accuracy, the Couchbase solution completed the accuracy test at 350 times the volume of queries handled by the challenger system.

"Scaling AI requires a developer database platform built for speed, throughput and reliability. With support for our Hyperscale Vector Indexing (HVI) and end-to-end RAG workflows, Couchbase stands out from other offerings in the market by providing more flexible and comprehensive vector search options," said Matt McDonough, SVP of product at Couchbase.

"By managing the full AI data lifecycle - which spans sourcing and vectorisation through LLM engagement, to validation and drift detection - we help customers create trustworthy agentic systems, while reducing latency, boosting recall accuracy and lowering total cost of ownership."

Couchbase 8.0 is available for both self-managed operations and the company's Capella-managed service and is deployable on-premises, in the cloud, at the edge, or across hybrid environments.

Industry perspectives

Customers and industry analysts provided perspectives on the update and its claimed effect on AI use cases. Ian Merrington, Chief Technology Officer at Seenit, commented:

"Couchbase's new vector search capabilities transform how we deliver context-aware video discovery for enterprises. We're already using SQL++ and full-text search to query metadata across hundreds of thousands of employee-generated videos, and added vector search capabilities takes this to the next level. Our customers can find relevant content based on meaning and context, not just exact keywords. As a Capella customer, we're excited for Couchbase 8.0 and the scalability and TCO benefits that make it the ideal solution for our AI-powered video platform."

Saurabh Jha, SVP and global head of data and analytics at Tech Mahindra, said:

"The single greatest accelerator for enterprise AI adoption is the simplification of the underlying data stack. Couchbase 8.0's launch is a pivotal milestone, collapsing the divide between operational data and the vector capabilities essential for modern AI. For our teams at Tech Mahindra, this means faster development cycles, lower architectural complexity and a direct path to deploying high-performance RAG and agentic AI solutions for our customers"

Security and compliance enhancements

Couchbase 8.0 introduces additional security and compliance-focused features to address CIO concerns. The platform now supports native data-at-rest encryption (DARE) by default, automatically encrypting data at rest and decrypting it as needed. Integration with the Key Management Interoperability Protocol (KMIP) is also included, aiming to simplify encryption key management across different environments.

The company has extended its cross-data centre replication (XDCR) feature to support mobile buckets, enabling mobile clients to synchronise with their nearest cluster - a move designed to bolster reliability, scalability, and compliance with data regulations for multinational businesses.

Additional operational resilience is provided by new intelligent auto-failover capabilities, which allow continued operation during various disruptions, such as when disk space is exhausted or ephemeral database buckets become unavailable.

Developer experience

Couchbase 8.0 includes improvements intended to enhance developer productivity, such as support for natural-language querying, allowing users who are not familiar with SQL++ to interact with the system using plain English queries. Other changes include a repository for query statistics to assist with troubleshooting, as well as improvements to the search engine, such as user-defined synonyms to improve search relevance.

Industry analysts highlighted the impact of these changes:

"Many of today's integrated vector databases take a generalised approach to indexing and retrieval, yet AI applications often have diverse performance and accuracy needs," said Devin Pratt, research director at IDC. "Solutions such as Couchbase demonstrate how multiple indexing options can help developers fine-tune vector search for their specific use cases, whether optimising for scale, combining hybrid search methods, or applying pre-filtered queries, offering greater flexibility than many other systems."

Kate Holterhoff, Senior Industry Analyst at RedMonk, added:

"The technical barrier to AI application development remains high, with many developers struggling to navigate complex database architectures and specialised query languages required for vector operations. This skills gap is becoming a bottleneck for organisations looking to scale their AI initiatives beyond pilot projects. Couchbase has introduced natural language querying capabilities and vector management in acknowledgement of the need to democratise and simplify AI development by making these powerful capabilities accessible to more developers, and especially those without deep database expertise."

Matt Aslett, Director of Research, Analytics and Data at ISG Software Research, said:

"Support for storing and indexing vectors has become a critical capability for data platform providers, enabling the development of applications infused with generative AI. Couchbase's support for multiple vector indexing and retrieval approaches delivers differentiation that enables developers to select the approach that best suits the requirements of each application."

Product features

Couchbase 8.0's vector data capabilities are delivered through three main indexing and retrieval methods: Hyperscale Vector Index, Composite Vector Index, and Search Vector Index. These are designed to offer high speed and capacity for a broad range of AI-driven use cases, providing the flexibility to optimise for performance, scale, or accuracy as required. The platform supports hybrid queries that can combine various data types and search styles within a single operation.

These additions are intended to help enterprises manage large-scale AI data needs more efficiently while addressing concerns around infrastructure cost, developer skills, security, and regulatory compliance.