DBMS > Faircom DB vs. H2GIS vs. Hazelcast vs. JanusGraph vs. UniData,UniVerse

System Properties Comparison Faircom DB vs. H2GIS vs. Hazelcast vs. JanusGraph vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

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

Spatial extension of H2

A widely adopted in-memory data grid

A Graph DBMS optimized for distributed clusters

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

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

Primary database model

Key-value store
Relational DBMS

Secondary database models

Relational DBMS

Document store

JSON support with IMDG 3.12

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

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

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	2.85
Rank	#98	Overall
	#1	Multivalue DBMS

Website

www.faircom.com/products/faircom-db

www.h2gis.org

hazelcast.com

janusgraph.org

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

Technical documentation

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

www.h2gis.org/docs/home

hazelcast.org/imdg/docs

docs.janusgraph.org

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

Developer

FairCom Corporation

CNRS

Hazelcast

Linux Foundation; originally developed as Titan by Aurelius

Rocket Software

Initial release

1979

2013

2008

2017

1985

Current release

V12, November 2020

5.3.6, November 2023

0.6.3, February 2023

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

LGPL 3.0

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

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++

Java

Server operating systems

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

easily portable to other OSs

All OS with a Java VM

Linux
OS X
Unix
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

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

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

yes

SQL-like query language

yes

APIs and other access methods

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

JCache
JPA
Memcached protocol
RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Java API

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

Supported programming languages

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

Java

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

Clojure
Java
Python

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

based on H2

yes

Event Listeners, Executor Services

yes

Triggers

yes

Events

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

Sharding

yes

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

based on H2

yes

Replicated Map

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

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 selectable by user

Raft Consensus Algorithm

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

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

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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

yes

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

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

based on H2

Role-based access control

User authentification and security via Rexster Graph Server

Access rights according to SQL-standard and operating system based

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