DBMS > Apache Solr vs. Ehcache vs. JaguarDB

System Properties Comparison Apache Solr vs. Ehcache vs. JaguarDB

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Editorial information provided by DB-Engines

Name

Description

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

A widely adopted Java cache with tiered storage options

Performant, highly scalable DBMS for AI and IoT applications

Primary database model

Search engine

Key-value store

Key-value store
Vector DBMS

Secondary database models

Spatial DBMS

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

Score	32.67
Rank	#24	Overall
	#3	Search engines

Score	4.22
Rank	#66	Overall
	#8	Key-value stores

Score	0.06
Rank	#358	Overall
	#53	Key-value stores
	#20	Vector DBMS

Website

solr.apache.org

www.ehcache.org

www.jaguardb.com

Technical documentation

solr.apache.org/resources.html

www.ehcache.org/documentation

www.jaguardb.com/support.html

Developer

Apache Software Foundation

Terracotta Inc, owned by Software AG

DataJaguar, Inc.

Initial release

2006

2009

2015

Current release

9.6.1, May 2024

3.10.0, March 2022

3.3 July 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL V3.0

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.

Implementation language

Java

C++

the server part. Clients available in other languages

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

Linux

Data scheme

yes

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

schema-free

yes

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

Java API
RESTful HTTP/JSON API

JCache

JDBC
ODBC

Supported programming languages

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

Java

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

Java plugins

Triggers

yes

User configurable commands triggered on index changes

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

Multi-source replication

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

Tunable Consistency (Strong, Eventual, Weak)

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

optimistic locking

yes

supports JTA and can work as an XA resource

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

rights management via user accounts

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