DBMS > DataFS vs. Infobright vs. Postgres-XL vs. Splice Machine

System Properties Comparison DataFS vs. Infobright vs. Postgres-XL vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Description

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.

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

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Object oriented DBMS

Relational DBMS

Secondary database models

Graph DBMS

Document store
Spatial DBMS

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

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

newdatabase.com

ignitetech.com/softwarelibrary/infobrightdb

www.postgres-xl.org

splicemachine.com

Technical documentation

dev.mobiland.com/Overview.xsp

www.postgres-xl.org/documentation

splicemachine.com/how-it-works

Developer

Mobiland AG

Ignite Technologies Inc.; formerly InfoBright Inc.

Splice Machine

Initial release

2018

2005

2014

since 2012, originally named StormDB

2014

Current release

1.1.263, October 2022

10 R1, October 2018

3.1, March 2021

License

Commercial or Open Source

commercial

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

Open Source

Mozilla public license

Open Source

AGPL 3.0, commercial license available

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

Java

Server operating systems

Windows

Linux
Windows

Linux
macOS

Linux
OS X
Solaris
Windows

Data scheme

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

yes

Typing

predefined data types such as float or date

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
JDBC
ODBC

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

JDBC
Native Spark Datasource
ODBC

Supported programming languages

.Net
C
C#
C++
VB.Net

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

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions

yes

Java

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

none

horizontal partitioning

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

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

Windows-Profile

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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More resources

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