DBMS > Ehcache vs. EJDB vs. JaguarDB vs. Kinetica

System Properties Comparison Ehcache vs. EJDB vs. JaguarDB vs. Kinetica

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Performant, highly scalable DBMS for AI and IoT applications

Fully vectorized database across both GPUs and CPUs

Primary database model

Key-value store

Document store

Key-value store
Vector DBMS

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#14	Vector DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Website

www.ehcache.org

github.com/Softmotions/ejdb

www.jaguardb.com

www.kinetica.com

Technical documentation

www.ehcache.org/documentation

github.com/Softmotions/ejdb/blob/master/README.md

www.jaguardb.com/support.html

docs.kinetica.com

Developer

Terracotta Inc, owned by Software AG

Softmotions

DataJaguar, Inc.

Kinetica

Initial release

2009

2012

2015

2012

Current release

3.10.0, March 2022

3.3 July 2023

7.1, August 2021

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

GPLv2

Open Source

GPL V3.0

commercial

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

C, C++

Server operating systems

All OS with a Java VM

server-less

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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.

Secondary indexes

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like DML and DDL statements

APIs and other access methods

JCache

in-process shared library

JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

Supported programming languages

Java

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Cache Event Listeners

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

none

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

GPU vRAM or System RAM

User concepts

Access control

rights management via user accounts

Access rights for users and roles on table level

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