What sets Vespa apart is that it combines deep customization with massive scalability. Almost everything you need to make data searchable is built in. Vespa is a mature, stable engine, and it has delivered rock-solid performance for our use cases over 7 years.

It also lets you take cutting-edge research from experiment to production. For example, Vespa supported late-interaction models such as ColBERT and ColPali well before most other search engines did, which made it the obvious choice when we wanted to bring those models into production. Thanks to Vespa’s modular architecture, we were able to build this on top of our existing search cluster with very little effort. Review collected by and hosted on G2.com.

Vespa has a steep learning curve, and the documentation can be hard to navigate at first. That said, it keeps improving. The sample apps repository covers a wide range of examples that make good starting points to build on. Combined with the Vespa Slack community, where the team and other users respond quickly, you get close to real-time help with troubleshooting.

Once you get the hang of it, Vespa becomes very easy to extend. Review collected by and hosted on G2.com.