Full-text search and analytics across large datasets in milliseconds.
Elasticsearch searches and analyses large datasets in milliseconds, including full text, fine-grained filters and a well-considered relevance ranking. At its core sits an inverted index that keeps finding terms fast regardless of data volume. That makes searching feel fast and accurate, even across millions of entries. We use it when search is a core feature rather than an afterthought.
More in the documentationWe use Elasticsearch when your users should search as they type, with typo tolerance, facets and sensible ordering. We also use it to gather logs and metrics from many services and make them searchable, so you are not poking around in the dark when something breaks.
{
"query": {
"match": {
"title": { "query": "databse", "fuzziness": "AUTO" }
}
}
}Good to know
Define the mapping of your fields deliberately before you ingest data. Let Elasticsearch guess everything dynamically and numbers or dates quickly land as text in the index, which you cannot fix afterwards without a reindex.
More tools we work with in the same area.
PostgreSQL
Our first choice for relational data, powerful and reliable.
MySQL & MariaDB
Proven relational databases for classic applications.
MS SQL Server
For enterprise environments and Microsoft integrations.
MongoDB
A flexible document database for unstructured or growing data.
Supabase
Postgres with auth, storage and realtime as a backend-as-a-service.
Redis
An ultra-fast key-value store for caching and realtime features.
You don't have to decide that, it's our job. Tell us about your plans.