DBMS > Faircom DB vs. Galaxybase vs. InfinityDB vs. SiteWhere

System Properties Comparison Faircom DB vs. Galaxybase vs. InfinityDB vs. SiteWhere

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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.

Scalable, ACID-compliant native distributed parallel graph platform

A Java embedded Key-Value Store which extends the Java Map interface

M2M integration platform for persisting/querying time series data

Primary database model

Key-value store
Relational DBMS

Graph DBMS

Key-value store

Time Series DBMS

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
	#40	Graph DBMS

Score	0.00
Rank	#383	Overall
	#59	Key-value stores

Score	0.07
Rank	#347	Overall
	#33	Time Series DBMS

Website

www.faircom.com/products/faircom-db

galaxybase.com

boilerbay.com

github.com/sitewhere/sitewhere

Technical documentation

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

boilerbay.com/infinitydb/manual

sitewhere1.sitewhere.io/index.html

Developer

FairCom Corporation

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Boiler Bay Inc.

SiteWhere

Initial release

1979

2017

2002

2010

Current release

V13, July 2024

Nov 20, November 2021

4.0

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

Common Public Attribution License Version 1.0

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++

C and Java

Java

Server operating systems

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

easily portable to other OSs

Linux

All OS with a Java VM

Linux
OS X
Windows

Data scheme

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

Strong typed schema

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

predefined scheme

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

APIs and other access methods

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

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

HTTP REST

Supported programming languages

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

Go
Java
Python

Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined procedures and functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

none

Sharding

based on HBase

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).

none

selectable replication factor

based on HBase

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

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

Optimistic locking for transactions; no isolation for bulk loads

Concurrency

Support for concurrent manipulation of data

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

Role-based access control

Users with fine-grained authorization concept

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