Lightweight, сlear, and great for both full-text and vector search

[Nawy]

I started using Manticore’s main text search engine and later tried its vector capabilities. I built a couple of proof-of-concepts at work combining vector and traditional search and it worked really well.

What I like most is that Manticore uses SQL, is very lightweight on servers, and easy to understand. The query language is straightforward and doesn’t feel “mystical” like in some other systems for example, Elasticsearch’s syntax can be quite unusual.

What I’d love to see in the future are more RAG-related features for instance, easier integration with AI embedding models, or even built-in vector generation directly inside Manticore.

Overall, I really like Manticore: it’s fast, simple, and well-documented. The only thing I’d add is better libraries for some languages like Rust (though I actually wrote my own connector for a PoC, and it worked just fine!).

Ivan Ermolaev
CEO at TaxSedate.com

[airolg]

Thank you for sharing your experience and for trying both the full-text and vector search features of Manticore!
We’re glad to hear that you find it lightweight, straightforward, and easy to work with — that simplicity and clarity are exactly what we aim for.

Your feedback about RAG integration and built-in vector generation is especially valuable. We’re continuously exploring ways to make AI and vector workflows more seamless, and insights like yours help guide that direction.

We also appreciate your honest comments about market visibility — that’s an area we’re actively working to improve. Hearing this from real users helps us understand where to focus our efforts.

Thanks again for taking the time to write such a thoughtful review and for spreading the word about Manticore in your work!