DBMS > BigObject vs. Faircom DB vs. Infobright vs. mSQL vs. Postgres-XL

System Properties Comparison BigObject vs. Faircom DB vs. Infobright vs. mSQL vs. Postgres-XL

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

mSQL (Mini SQL) is a simple and lightweight RDBMS

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

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

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

bigobject.io

www.faircom.com/products/faircom-db

ignitetech.com/softwarelibrary/infobrightdb

hughestech.com.au/products/msql

www.postgres-xl.org

Technical documentation

docs.bigobject.io

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

www.postgres-xl.org/documentation

Developer

BigObject, Inc.

FairCom Corporation

Ignite Technologies Inc.; formerly InfoBright Inc.

Hughes Technologies

Initial release

2015

1979

2005

1994

2014

since 2012, originally named StormDB

Current release

V12, November 2020

4.4, October 2021

10 R1, October 2018

License

Commercial or Open Source

commercial

free community edition available

commercial

Restricted, free version available

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

commercial

free licenses can be provided

Open Source

Mozilla public license

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++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

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

easily portable to other OSs

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
macOS

Data scheme

yes

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

yes

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes, ANSI SQL with proprietary extensions

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

distributed, parallel query execution

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

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

ADO.NET
JDBC
ODBC

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

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

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

Lua

yes

.Net, JavaScript, C/C++

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

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

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

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