Mobile app developers know that a key to adoption is engaging users with an experience that is unique and tailored just for them. This means the app must display items and data in context with the user’s tastes, history, location, habits and other information to make a personal connection, the more it can provide this sort of experience the more engaged users become.

Search is a ubiquitous means of user interaction in apps, and as such should always return personalized responses in order to make an impact. But searching only for specific words and phrases is not enough to produce accurate results in context. To make a personal connection you need semantic search for matches that are meaningful to the user. This is where vector search comes in.

Vector search goes beyond simply finding matching words, it finds related information based on the meaning of a search query, making it the best option for providing relevant information that connects with users.

Vector search also makes output from generative AI more personal by enabling Retrieval Augmented Generation, or “RAG”, where local vectorized data is passed along with prompts to provide better precision and context for LLM responses.

In fact, vector search features are being added to nearly every cloud database, so how is Couchbase doing it differently? By offering vector search from cloud to edge.

Vector search at the edge

Other database vendors only offer vector search in the cloud, making the functionality subject to internet latency, and rendering it useless without connectivity — not good for mobile apps! What’s needed is a way to take advantage of vector search at the edge without being dependent on the internet.

Couchbase Mobile is the answer. 

Couchbase Mobile is a mobile database platform that includes:

A cloud database

Available as a fully managed and hosted Database as a Service with Couchbase Capella, or deploy and host Couchbase Server on your own.

An embedded database

Couchbase Lite is the embeddable version of Couchbase for mobile and IoT apps that stores data locally on the device.

Data synchronization

A secure gateway for data sync over the web, as well as peer-to-peer sync between devices. Offered as fully hosted and managed sync with Capella App Services, or install and manage Couchbase Sync Gateway yourself.

Because Couchbase Lite runs directly on the edge devices, it eliminates dependencies on the internet, which makes apps faster and more reliable. Couchbase Lite now supports vector embedding and vector search that can be called using SQL, enabling this must-have feature to be run locally as an offline-first capability. And automatic sync ensures data is instantly shared across the app ecosystem to Couchbase Capella and Couchbase Server whenever connectivity is available.

Running vector search on-device brings all the benefits of edge computing for apps including ultra-low latency, guaranteed availability even when offline, bandwidth savings, and customized LLM responses, all without compromising data privacy – sensitive data never has to leave the device! 

And these benefits are amplified when combined with vector search in Couchbase Capella and Couchbase Server, enabling cloud to edge vector support.

Sign up for the beta!

Vector search in Couchbase Lite is coming in beta, sign up for access today!

Accepted participants get access to Couchbase Lite beta software and documentation, regular check-ins with Couchbase Product Managers and Engineering, and an open channel to Couchbase for questions and feedback.

Be among the first to innovate with Couchbase Mobile, the database platform with cloud-to-edge-to-device vector search!

Author

Posted by Mark Gamble, Dir Product & Solutions Mktg, Couchbase

I am a passionate product marketer with a technical and solution consulting background and 20+ years of experience in Enterprise and Open Source technology. I have launched several database and analytic solutions throughout my career, and have worked with customers across a wide variety of industries including Financial Services, Automotive, Hospitality, High-Tech and Healthcare. I have particular expertise in analytics and AI, love all things data, and am an emphatic supporter of data-for-good initiatives.

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