DBMS > EJDB vs. FatDB vs. Hazelcast vs. RDFox vs. TimesTen

System Properties Comparison EJDB vs. FatDB vs. Hazelcast vs. RDFox vs. TimesTen

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

A widely adopted in-memory data grid

High performance knowledge graph and semantic reasoning engine

In-Memory RDBMS compatible to Oracle

Primary database model

Document store

Document store
Key-value store

Key-value store

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Relational DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	0.23
Rank	#308	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

github.com/Softmotions/ejdb

hazelcast.com

www.oxfordsemantic.tech

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

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

hazelcast.org/imdg/docs

docs.oxfordsemantic.tech

docs.oracle.com/database/timesten-18.1

Developer

Softmotions

FatCloud

Hazelcast

Oxford Semantic Technologies

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2012

2008

2017

1998

Current release

5.3.6, November 2023

6.0, Septermber 2022

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

GPLv2

commercial

Open Source

Apache Version 2; commercial licenses available

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++

Server operating systems

server-less

Windows

All OS with a Java VM

Linux
macOS
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

RDF schemas

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.

yes

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

Via inetgration in SQL Server

SQL-like query language

yes

APIs and other access methods

in-process shared library

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JCache
JPA
Memcached protocol
RESTful HTTP API

RESTful HTTP API
SPARQL 1.1

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

C
Java

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

via applications

yes

Event Listeners, Executor Services

PL/SQL

Triggers

yes

via applications

yes

Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

yes

Replicated Map

replication via a shared file system

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

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

one or two-phase-commit; repeatable reads; read commited

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

User concepts

Access control

Can implement custom security layer via applications

Role-based access control

Roles, resources, and access types

fine grained access rights according to SQL-standard

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