Elasticsearch vs PostgreSQL

Elasticsearch and PostgreSQL are both listed under Databases in the DevPages directory. This page puts the details we hold for each of them side by side.

It does not score them and does not pick a winner. Fields the catalog has no value for say “Not recorded” rather than being filled in with a guess.

Elasticsearch, PostgreSQL compared field by field. Values are taken from the DevPages catalog; fields we hold no value for read “Not recorded”.
	Elasticsearch	PostgreSQL
Category	Databases	Databases
Pricing model	Freemium	Open Source
Open source	Yes	Yes
GitHub stars	77.9K	21.8K
Key features	Full-text search with relevance scoring Distributed architecture and clustering Real-time data ingestion and indexing Powerful aggregations and analytics Multi-tenancy and security features RESTful API and JSON documents Machine learning capabilities Geospatial and time-series support	ACID compliance and transactions Advanced SQL features and window functions JSON and JSONB data types Full-text search capabilities Geospatial data support with PostGIS Custom data types and functions Streaming replication and high availability Extensive indexing options
Use cases	Application and website search Log and event data analysis Business intelligence and analytics Security information and event management E-commerce product search Real-time application monitoring Geospatial data analysis Machine learning and AI applications	Web application backends Data warehousing and analytics Geospatial applications Financial and e-commerce systems Content management systems Time-series data storage Multi-tenant applications Enterprise data management
Integrations	Kibana Logstash Beats Java Python Node.js Spring Data Docker	Django Rails Node.js Java Python Kubernetes Docker Grafana
Tags	search analytics full-text distributed lucene elk-stack	sql relational acid json geospatial full-text-search
Links	Website (opens in a new tab) GitHub (opens in a new tab) Docs (opens in a new tab)	Website (opens in a new tab) GitHub (opens in a new tab) Docs (opens in a new tab)

What each one is

Elasticsearch

Distributed search and analytics engine built on Apache Lucene

Elasticsearch is a distributed, RESTful search and analytics engine capable of addressing a growing number of use cases. Built on Apache Lucene, it provides a distributed, multitenant-capable full-text search engine with an HTTP web interface and schema-free JSON documents. It's the heart of the Elastic Stack.

Full Elasticsearch listing

PostgreSQL

Advanced open-source relational database with powerful features

PostgreSQL is a powerful, open-source object-relational database system with a strong reputation for reliability, feature robustness, and performance. It supports both SQL and JSON querying, making it a versatile choice for modern applications. PostgreSQL offers advanced features like custom data types, full-text search, and geospatial data support.

Full PostgreSQL listing

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Elasticsearch vs PostgreSQL

Elasticsearch and PostgreSQL are both listed under Databases in the DevPages directory. This page puts the details we hold for each of them side by side.

It does not score them and does not pick a winner. Fields the catalog has no value for say “Not recorded” rather than being filled in with a guess.

Elasticsearch, PostgreSQL compared field by field. Values are taken from the DevPages catalog; fields we hold no value for read “Not recorded”.
	Elasticsearch	PostgreSQL
Category	Databases	Databases
Pricing model	Freemium	Open Source
Open source	Yes	Yes
GitHub stars	77.9K	21.8K
Key features	Full-text search with relevance scoring Distributed architecture and clustering Real-time data ingestion and indexing Powerful aggregations and analytics Multi-tenancy and security features RESTful API and JSON documents Machine learning capabilities Geospatial and time-series support	ACID compliance and transactions Advanced SQL features and window functions JSON and JSONB data types Full-text search capabilities Geospatial data support with PostGIS Custom data types and functions Streaming replication and high availability Extensive indexing options
Use cases	Application and website search Log and event data analysis Business intelligence and analytics Security information and event management E-commerce product search Real-time application monitoring Geospatial data analysis Machine learning and AI applications	Web application backends Data warehousing and analytics Geospatial applications Financial and e-commerce systems Content management systems Time-series data storage Multi-tenant applications Enterprise data management
Integrations	Kibana Logstash Beats Java Python Node.js Spring Data Docker	Django Rails Node.js Java Python Kubernetes Docker Grafana
Tags	search analytics full-text distributed lucene elk-stack	sql relational acid json geospatial full-text-search
Links	Website (opens in a new tab) GitHub (opens in a new tab) Docs (opens in a new tab)	Website (opens in a new tab) GitHub (opens in a new tab) Docs (opens in a new tab)

Elasticsearch

PostgreSQL