An Erlang client for Elasticsearch's REST API, enabling seamless integration of Elasticsearch into Erlang/OTP applications.
ErlasticSearch is an Erlang client library for Elasticsearch that enables Erlang applications to communicate with Elasticsearch clusters via its REST API. It provides functions for indexing documents, creating indices, and performing searches, acting as a bridge between Erlang's concurrent processing model and Elasticsearch's powerful search capabilities.
Erlang developers building applications that require full-text search, log analysis, or data indexing capabilities using Elasticsearch as the backend search engine.
Developers choose ErlasticSearch for its native Erlang integration, configurable JSON library support, and straightforward API that simplifies Elasticsearch operations within Erlang/OTP systems without needing external HTTP clients.
An Erlang app for communicating with Elastic Search's rest interface.
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Configurable to work with different JSON libraries like jsx or jiffy by setting the ERLASTIC_SEARCH_JSON_MODULE environment variable, allowing seamless integration into existing Erlang projects.
Includes functions for creating indices, indexing documents, and executing searches, covering essential Elasticsearch operations as demonstrated in the README examples.
Provides a Docker-based testing setup with Elasticsearch and optional Kibana, making development and validation straightforward and reproducible.
Offers a simple, native Erlang interface that prioritizes interoperability, fitting well into Erlang/OTP applications without heavy dependencies.
Switching from the default jsx requires compiling with environment variables and ensuring custom modules implement encode/decode callbacks, adding setup complexity and potential errors.
The README focuses on basic operations; it may not support all Elasticsearch REST API endpoints, such as bulk operations or complex queries, forcing developers to extend the client themselves.
Beyond basic examples, there's limited guidance on error handling, performance tuning, or production deployment, which could hinder adoption for complex use cases.