DBMS > EJDB vs. GigaSpaces vs. JaguarDB

System Properties Comparison EJDB vs. GigaSpaces vs. JaguarDB

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Editorial information provided by DB-Engines

Name

Description

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

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Performant, highly scalable DBMS for AI and IoT applications

Primary database model

Document store

Document store
Object oriented DBMS

Values are user defined objects

Key-value store
Vector DBMS

Secondary database models

Graph DBMS
Search engine

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Trend Chart

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Website

github.com/Softmotions/ejdb

www.gigaspaces.com

www.jaguardb.com

Technical documentation

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

docs.gigaspaces.com/latest/landing.html

www.jaguardb.com/support.html

Developer

Softmotions

Gigaspaces Technologies

DataJaguar, Inc.

Initial release

2012

2000

2015

Current release

15.5, September 2020

3.3 July 2023

License

Commercial or Open Source

Open Source

GPLv2

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++, .Net

C++

the server part. Clients available in other languages

Server operating systems

server-less

Linux
macOS
Solaris
Windows

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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

in-process shared library

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

JDBC
ODBC

Supported programming languages

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

.Net
C++
Java
Python
Scala

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

Server-side scripts

Stored procedures

yes

Triggers

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

Role-based access control

rights management via user accounts

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