DBMS > FatDB vs. JaguarDB vs. Oracle Berkeley DB vs. STSdb vs. TerminusDB

System Properties Comparison FatDB vs. JaguarDB vs. Oracle Berkeley DB vs. STSdb vs. TerminusDB

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

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

Performant, highly scalable DBMS for AI and IoT applications

Widely used in-process key-value store

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Document store
Key-value store

Key-value store
Vector DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Key-value store

Graph DBMS

Secondary database models

Document store
RDF store

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

Score	0.09
Rank	#356	Overall
	#53	Key-value stores
	#13	Vector DBMS

Score	2.52
Rank	#114	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	0.06
Rank	#365	Overall
	#55	Key-value stores

Score	0.22
Rank	#323	Overall
	#28	Graph DBMS

Website

www.jaguardb.com

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

github.com/STSSoft/STSdb4

terminusdb.com

Technical documentation

www.jaguardb.com/support.html

docs.oracle.com/cd/E17076_05/html/index.html

terminusdb.github.io/terminusdb/#

Developer

FatCloud

DataJaguar, Inc.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

STS Soft SC

DataChemist Ltd.

Initial release

2012

2015

1994

2011

2018

Current release

3.3 July 2023

18.1.40, May 2020

4.0.8, September 2015

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

Open Source

commercial license available

Open Source

GPLv2, commercial license available

Open Source

GPL V3

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

C++

the server part. Clients available in other languages

C, Java, C++ (depending on the Berkeley DB edition)

Prolog, Rust

Server operating systems

Windows

Linux

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Windows

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

Via inetgration in SQL Server

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

SQL interfaced based on SQLite is available

SQL-like query language (WOQL)

APIs and other access methods

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

JDBC
ODBC

.NET Client API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

C#
Java

JavaScript
Python

Server-side scripts

Stored procedures

yes

via applications

yes

Triggers

yes

via applications

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

Source-replica replication

none

Journaling Streams

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

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

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

rights management via user accounts

Role-based access control

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