DBMS > Apache Solr vs. OpenSearch

System Properties Comparison Apache Solr vs. OpenSearch

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Our visitors often compare Apache Solr and OpenSearch with Elasticsearch, Typesense and PostgreSQL.

Editorial information provided by DB-Engines

Name

Description

A widely used distributed, scalable search engine based on Apache Lucene

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Primary database model

Search engine

Search engine
Vector DBMS

Secondary database models

Spatial DBMS

Vector DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	32.79
Rank	#23	Overall
	#3	Search engines

Score	17.38
Rank	#32	Overall
	#4	Search engines
	#2	Vector DBMS

Website

solr.apache.org

github.com/opensearch-project
opensearch.org

Technical documentation

solr.apache.org/resources.html

opensearch.org/docs/latest

Developer

Apache Software Foundation

The OpenSearch Software Foundation

Initial release

2006

2021

Current release

9.6.1, May 2024

2.19, February 2025

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

STACKIT OpenSearch offers OpenSearch in a managed version in enterprise grade, 100% GDPR-compliant, for a wide range of applications like analytics, website search, offering scalability and fast data access.

Implementation language

Java

Server operating systems

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

All OS with a Java VM

Data scheme

yes

Dynamic Fields enables on-the-fly addition of new fields

schema-free

Flexible type definitions. Once a type is defined, it is persistent

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

All search fields are automatically indexed

SQL

Support of SQL

Solr Parallel SQL Interface

SQL-like query language

APIs and other access methods

Java API
RESTful HTTP/JSON API

Supported programming languages

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

Server-side scripts

Stored procedures

Java plugins

yes

Triggers

yes

User configurable commands triggered on index changes

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

yes

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