Couchbase 8.0 accelerates enterprise AI with faster vector search

Couchbase has launched version 8.0 of its data platform, introducing enhanced support for large-scale AI applications through new vector indexing, improved security, and features designed to boost developer productivity.

With AI adoption accelerating across industries, many organisations have struggled to operationalise new technology, with data access and management cited as significant obstacles. In recent Couchbase research, 28% of chief information officers indicated that challenges with data were slowing AI project progress and just 16% currently have a vector database capable of fully supporting emerging large-scale AI workloads.

Vector search at scale

Couchbase 8.0 brings a suite of vector indexing and retrieval options designed to support a wide range of AI workloads. The platform's Hyperscale Vector Indexing (HVI) achieves search across billions of vectors with millisecond latency and tunable recall accuracy. It is available both on-premise and via Couchbase's Capella cloud service, and supports deployments extending to the network edge.

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. 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 commissioned independent benchmarks to compare the performance of HVI. The platform reached up to 19,057 queries per second with 28-millisecond latency at 66% recall accuracy, considerably outpacing a leading challenger in the market, which performed just six queries per second at 57% recall accuracy. When the test was adjusted for accuracy, the HVI delivered more than 700 queries per second with 93% recall accuracy.

Real-world use

Couchbase's technical improvements have already found application in customer use cases. Ian Merrington, Chief Technology Officer at Seenit, commented on how the platform is helping to enhance context-aware video search for enterprises.

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.

The announcement was also welcomed by Tech Mahindra, a technology consultancy and services provider. Saurabh Jha, Senior Vice President 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

The release includes native data-at-rest encryption and extended cross data centre replication to mobile data buckets, improving both resilience and compliance for organisations operating in regulated sectors or across multiple jurisdictions.

The platform provides built-in encryption for stored data, support for the Key Management Interoperability Protocol for encryption key handling, and expanded intelligent auto-failover so that mission-critical workloads remain available through infrastructure issues. These enhancements address concerns identified in Couchbase's research, where over a third of CIOs said that meeting security or compliance requirements had hindered AI developments.

Developer improvements and simplified AI integration

Couchbase 8.0 also targets productivity, offering a natural language interface for query writing, which can make the platform more accessible for those without deep database expertise. Other updates include a query workload repository, user-defined synonyms in the search engine, and features to streamline troubleshooting and operational management.

Industry analysts recognise the impact of these features. Devin Pratt, Research Director at IDC, said:

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. 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.

Platform availability

Couchbase continues to support application development across operational, analytical, AI and mobile data with a platform that can be deployed on-premises, in Kubernetes, or via the cloud. The company states that this approach helps to simplify development while containing costs for organisations building and maintaining AI-powered applications at scale.