DBMS > Altibase vs. DataFS vs. Faircom DB vs. JanusGraph vs. LokiJS

System Properties Comparison Altibase vs. DataFS vs. Faircom DB vs. JanusGraph vs. LokiJS

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

In-memory JavaScript DBMS

Primary database model

Relational DBMS

Object oriented DBMS

Key-value store
Relational DBMS

Graph DBMS

Document store

Secondary database models

Graph DBMS

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

Score	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Website

altibase.com

newdatabase.com

www.faircom.com/products/faircom-db

janusgraph.org

github.com/techfort/LokiJS

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

dev.mobiland.com/Overview.xsp

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

docs.janusgraph.org

techfort.github.io/LokiJS

Developer

Altibase

Mobiland AG

FairCom Corporation

Linux Foundation; originally developed as Titan by Aurelius

Initial release

1999

2018

1979

2017

2014

Current release

v7.3, 2023, August 2023

1.1.263, October 2022

V12, November 2020

0.6.3, February 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

Restricted, free version available

Open Source

Apache 2.0

Open Source

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++

ANSI C, C++

Java

JavaScript

Server operating systems

AIX
HP-UX
Linux

Windows

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

easily portable to other OSs

Linux
OS X
Unix
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

yes

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

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

via views

SQL

Support of SQL

ANSI SQL-92

yes, ANSI SQL with proprietary extensions

APIs and other access methods

JDBC
ODBC
Proprietary protocol

.NET Client API
Proprietary client DLL
WinRT client

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

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JavaScript API

Supported programming languages

C
C++
Java

.Net
C
C#
C++
VB.Net

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

Clojure
Java
Python

JavaScript

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

.Net, JavaScript, C/C++

yes

View functions in JavaScript

Triggers

yes

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Proprietary Sharding system

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Eventual Consistency
Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

ACID

atomic operations within a single collection possible

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

Windows-Profile

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

User authentification and security via Rexster Graph Server

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More resources

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