Elasticsearch is a consistent leader in the DB-Engines rankings

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There are many differences between Elasticsearch and Sphinx. Here are the most important ones.

Scalability. Like Sphinx, ES offers a high degree of horizontal scalability, allowing you to distribute and replicate data across multiple nodes and shards. However, Sphinx requires manual management of the index structure, while Elasticsearch allows you kazakhstan telegram number database to add new nodes to an existing system on the fly and automatically distribute the load across them.

API capabilities. ES supports a wide range of complex queries and powerful aggregation and filtering functions for data analysis, and can return data directly from the search engine. Sphinx has a poorer API, which forces you to constantly yank its database with queries.

Data structure. ES works better with multilingual systems and unstructured data, while Sphinx indexes structured databases faster: forums, online stores, chats, catalogs. For multilingual systems, in the case of Sphinx, you will have to build separate indexes for different languages, separately configure morphology, stemming, fuzzy search parameters. Elasticsearch, on the contrary, will analyze and upload data to a separate index, configure parameters for the required language. The data will be isolated, and the search will work faster. Effective work with unstructured data allows you to successfully use ES in recommender systems.

Fault tolerance. Sphinx does not support automatic replication and sharding management, which makes it less resilient to failures compared to Elasticsearch, increasing the workload on system administrators.