DBMS > Apache Solr vs. ReductStore vs. Typesense

System Properties Comparison Apache Solr vs. ReductStore vs. Typesense

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Editorial information provided by DB-Engines

Name

Description

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

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Search engine

Time Series DBMS

Search engine

Secondary database models

Spatial DBMS

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

Score	32.79
Rank	#23	Overall
	#3	Search engines

Score	0.06
Rank	#355	Overall
	#37	Time Series DBMS

Score	0.92
Rank	#192	Overall
	#14	Search engines

Website

solr.apache.org

github.com/reductstore
www.reduct.store

typesense.org

Technical documentation

solr.apache.org/resources.html

www.reduct.store/docs

typesense.org/docs

Developer

Apache Software Foundation

ReductStore LLC

Initial release

2006

2023

2015

Current release

9.6.1, May 2024

1.9, March 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Business Source License 1.1

Open Source

GPL V3

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.

Implementation language

Java

C++, Rust

C++

Server operating systems

All OS with a Java VM

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

Docker
Linux
macOS
Windows

Linux

Data scheme

yes

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

schema-free

pre-defined schema optional

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

SQL

Support of SQL

Solr Parallel SQL Interface

APIs and other access methods

Java API
RESTful HTTP/JSON API

HTTP API

RESTful HTTP API

Supported programming languages

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

C++
JavaScript (Node.js)
Python
Rust

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using RAFT

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

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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