All Stories

Billion-scale vector search with Vespa - part one

Part one in a blog post series on billion-scale vector search. This post covers using nearest neighbor search with compact binary representations and bitwise hamming distance.

Text-to-image search with Vespa

In this post we explore a text-to-image search application on Vespa using approximate nearest neighbor search on vector representations of text and images.

Vespa Newsletter, November 2021

Advances in Vespa features and performance include improved schema inheritance, Intellij plugin for schemas, Hamming distance in ranking, and performance gains in data dump and application deployment.

Vespa increases HTTP visiting throughput ten-fold or more

The new slicing feature in /document/v1 splits visiting across independent HTTP requests, letting throughput scale with the number of container nodes or clients.

Result diversification using Vespa result grouping

This blog post dives into how to achieve result diversification using Vespa's grouping framework.

Vespa Product Updates, September 2021

Advances in Vespa features and performance include Vespa CLI, nearest neighbor performance improvements, mTLS security, improved write throughput and Sentencepiece Encoder.

Computing with tensors in Vespa

In this blog post, we'll explore some of the unique properties of tensors in Vespa.

Introducing Vespa CLI

The official command-line tool for Vespa is now available.

Securing Vespa with mutually authenticated TLS (mTLS)

Learn how to secure both the application container and the Vespa internal communication of your Vespa application.

Internship at Vespa

After the summer internship of 2021 the interns have summarised what they have done and their experience at Vespa

Vespa Product Updates, July 2021

Advances in Vespa features and performance include HTTP/2 feed and query endpoints, ONNX Runtime integration for stateless model inference, and the new open Vespa Factory build and test system.

Accelerating stateless model evaluation on Vespa

It has become increasingly important to efficiently evaluate machine-learned models in the stateless container cluster. We have recently added accelerated model evaluation here, which opens up new usage areas.