It’s not particularly difficult to setup for full text search backend + API: solr, elasticsearch, typesense, or couchbase are good document oriented solutions that pretty much work out of the box. Postgres or mysql have decent support for full-text search if you’re already on either, though you’ll need to integrate some sort of API layer.
There’s plenty of managed versions of the document oriented too. The biggest issue with Algolia, imo, is they charge per search request. e.g. if you enable autocomplete, every single key press costs you money and they don’t offer a particularly unique product.
If your dataset is small enough or you have plenty of resources, and you don’t need any fancy customizabilty and multitenancy (always searching only a subset of all documents, filtered by tenant ID) then Typesense.
Otherwise if Typesense can’t fit the index in your RAM it will not work, if you need to filter every search it will become slow.
If you need lots of customizability of how you index your documents and how you search, what you prioritize in the search, facets, nothing beats Elastic here. But it will need plenty of resources or otherwise it will be slow.
If you need fast but absolutely non customizable search that can live off a lot less than 1GB of RAM (less than 100MBs even) then you might have some success with https://github.com/valeriansaliou/sonic
If you’re constrained on resources but sonic is too limiting, then finally you might have some success with Manticore search. It’s featureful but using it with different languages can be a lot of work (I’m not sure why they don’t ship a distribution with all language plugins enabled and configured), the docs will be good enough to get you started. It can live off a few hundred MBs of RAM with large indexes, and will still be faster than Elastic.
Terms will be common across the group. The scoped API key helps you guarantee that you can never accidentally access another customer's search data since the filter condition will be baked into the query itself and you also use a separate key per customer.
We offer a hosted/managed app search experience on top of Elastic or OpenSearch with appbase.io.
You can leverage the best of Elasticsearch (state-of-the-art) engine while getting Algolia like features like search relevance control plane, query rules, out-of-the-box analytics / insights, caching, UI components across all FE platforms (React, Vue, React Native, Flutter).
There’s plenty of managed versions of the document oriented too. The biggest issue with Algolia, imo, is they charge per search request. e.g. if you enable autocomplete, every single key press costs you money and they don’t offer a particularly unique product.