DBMS > Faircom DB vs. H2GIS vs. Hazelcast vs. Newts

System Properties Comparison Faircom DB vs. H2GIS vs. Hazelcast vs. Newts

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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

Time Series DBMS based on Cassandra

Primary database model

Key-value store
Relational DBMS

Spatial DBMS

Key-value store

Time Series 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	0.18
Rank	#314	Overall
	#45	Key-value stores
	#141	Relational DBMS

Score	0.00
Rank	#385	Overall
	#7	Spatial DBMS

Score	5.72
Rank	#59	Overall
	#6	Key-value stores

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

www.faircom.com/products/faircom-db

www.h2gis.org

hazelcast.com

opennms.github.io/newts

Technical documentation

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

www.h2gis.org/docs/home

hazelcast.org/imdg/docs

github.com/OpenNMS/newts/wiki

Developer

FairCom Corporation

CNRS

Hazelcast

OpenNMS Group

Initial release

1979

2013

2008

2014

Current release

V13, July 2024

5.3.6, November 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

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
Windows

Data scheme

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

yes

schema-free

Typing

predefined data types such as float or date

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.

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

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

HTTP REST
Java 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

Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

based on H2

yes

Event Listeners, Executor Services

Triggers

yes

Events

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

Sharding

based on Cassandra

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

selectable replication factor

based on Cassandra

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
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

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

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

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

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