Compare Typesense to other search engines:
- Compare - Typesense vs Algolia vs Elasticsearch vs Meilisearch Comparison
- Compare - How does this differ from Elasticsearch?
- Compare - How does this differ from Algolia?
typesense online running examples / live demos (souce):
- Search a 32M songs dataset from MusicBrainz: songs-search.typesense.org
- Search a 28M books dataset from OpenLibrary: books-search.typesense.org
- Search a 2M recipe dataset from RecipeNLG: recipe-search.typesense.org
- Search 1M Git commit messages from the Linux Kernel: linux-commits-search.typesense.org
- Spellchecker with type-ahead, with 333K English words: spellcheck.typesense.org
- An E-Commerce Store Browsing experience: ecommerce-store.typesense.org
Speed is great, but what about the memory footprint?
A fresh Typesense server will consume about 30 MB of memory. As you start indexing documents, the memory use will increase correspondingly. How much it increases depends on the number and type of fields you index.
We've strived to keep the in-memory data structures lean. To give you a rough idea: when 1 million Hacker News titles are indexed along with their points, Typesense consumes 165 MB of memory. The same size of that data on disk in JSON format is 88 MB. If you have any numbers from your own datasets that we can add to this section, please send us a PR!
- A dataset containing 2.2 Million recipes (recipe names and ingredients):
- Took up about 900MB of RAM when indexed in Typesense
- Took 3.6mins to index all 2.2M records
- On a server with 4vCPUs, Typesense was able to handle a concurrency of 104 concurrent search queries per second, with an average search processing time of 11ms.
- A dataset containing 28 Million books (book titles, authors and categories):
- Took up about 14GB of RAM when indexed in Typesense
- Took 78mins to index all 28M records
- On a server with 4vCPUs, Typesense was able to handle a concurrency of 46 concurrent search queries per second, with an average search processing time of 28ms.
- With a dataset containing 3 Million products (Amazon product data), Typesense was able to handle a throughput of 250 concurrent search queries per second on an 8-vCPU 3-node Highly Available Typesense cluster.