DBMS > EJDB vs. Faircom DB vs. GBase vs. TimesTen vs. UniData,UniVerse

System Properties Comparison EJDB vs. Faircom DB vs. GBase vs. TimesTen vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

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

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

In-Memory RDBMS compatible to Oracle

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Document store

Key-value store
Relational DBMS

Relational DBMS

Multivalue DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

github.com/Softmotions/ejdb

www.faircom.com/products/faircom-db

www.gbase.cn

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

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

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

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

docs.oracle.com/database/timesten-18.1

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Softmotions

FairCom Corporation

General Data Technology Co., Ltd.

Oracle, TimesTen Performance Software, HP

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

Rocket Software

Initial release

2012

1979

2004

1998

1985

Current release

V12, November 2020

GBase 8a, GBase 8s, GBase 8c

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

GPLv2

commercial

Restricted, free version 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

ANSI C, C++

C, Java, Python

Server operating systems

server-less

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux

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

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

schema free, schema optional, schema required, partial schema,

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes, ANSI SQL Types, JSON, typed binary structures

yes

optional

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

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

Standard with numerous extensions

yes

APIs and other access methods

in-process shared library

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

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

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

C
C++
Java
PL/SQL

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined functions

PL/SQL

yes

Triggers

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

horizontal partitioning (by range, list and hash) and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

yes

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate 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

tunable from ACID to Eventually Consistent

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

yes

by means of logfiles and checkpoints

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

Fine grained access rights according to SQL-standard with additional protections for files

yes

fine grained access rights according to SQL-standard

Access rights according to SQL-standard and operating system based

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