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Vector Search
What's Vector Search and why is it important?
Get a quick overview of vectors, vector search, use cases, and key features.
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What is vector search?
Vector search delivers nearest-neighbor results, without needing a direct match. Text, images, audio, and video are converted to mathematical representations and used for semantic searching or overcoming GenAI challenges using the retrieval-augmented generation (RAG) framework.
Don’t let these vector search challenges slow you down
Complexity
There is no need to use a separate database for vector search, adding complexity, administration, cost, and latency of the overall app.
Latency
Returning results as fast as possible is critical to users. Extra hops and poor indexing kills user experience.
Security
Build GenAI apps without feeding corporate data to public models and deliver users accurate and up-to-date results.
Scalability
Avoid needing to architect your app when it moves into the real world. Choose a database that scales globally with millisecond response times.
Vector search key capabilities
Building powerful vector and GenAI-based applications requires a powerful database platform with a differentiated architecture that is fast, affordable, versatile, and as easy as SQL. Couchbase helps developers build apps using vector search and working with LangChain and LlamaIndex to leverage the AI ecosystem.
Single platform for modern applications
Build modern applications, supporting GenAI, vector search, and in-memory speeds, with flexible JSON and data structures in a single platform and SQL++.
Hybrid search for the real world
Support vector, full-text, ranges, predicate, and geolocation with a single SQL query and a single index, for real-world use cases with low latency.
Highly scalable
Benefit from Couchbase’s industry-leading price performance and ability to flexibly grow Search and Index Services to any scale.
Cloud-to-edge support
Data is created and consumed at the edge. Couchbase was the first to announce vector support in our embeddable Couchbase Lite database. Join the beta program.
Similarity search, hybrid search
Similarity is a powerful tool for users to find products and information, but many real-world scenarios have users wanting to search across a variety of methods, like text, geolocations, ranges, and include operational data too. Couchbase lets developers build powerful search functionality to delight users.
GenAI apps and RAG
Generative AI has proven to be a game-changer in how users interact with information and applications, but it is not without limitations. Using RAG, teams can make GenAI safer, more accurate, and up to date.
Fraud and anomaly detection
By converting user behavior and transactions into vectors, those patterns can be compared to other similar vector representations that might indicate fraud. Vector search is effective in handling high-dimensional data and similarity matching.
Mobile vector apps
Running vector search in mobile and embedded devices comes with all the benefits of edge computing including millisecond response times, reliability, availability even without the internet (“offline mode”), bandwidth savings, and most importantly, customized responses without compromising on data privacy.
Adaptive applications
Adaptive applications can adjust their behavior and features in real time based on various factors, such as user preferences, environmental conditions, data inputs, or changing circumstances. The goal of adaptive applications is to provide a hyper-personalized and responsive user experience by dynamically tailoring their functionality to the specific needs and current context of the user.
What customers are saying
“With search integrated into Couchbase, we can seamlessly search all this data and derive relevance-based intelligence using a single data platform.”
“Couchbase Search allows us to deliver customer search results from extremely large data sets very efficiently.”
“Couchbase is a trifecta of value. We get more features, save time, and spend less money all at once.”
“Couchbase provides a solution no others do. It gives us the modularity we need with immediate operational simplicity, high performance, and scalability.”
Introduction to vector search
See an adaptive application in action
Learn about the power of vector databases
Start building
Check out our developer portal to explore NoSQL, browse resources, and take Couchbase for a spin in our playground.
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Try Capella iQ
Use our generative AI-powered coding assistant to create sample data, refine it, and build queries on the datasets.