DBMS > DataFS vs. Ignite vs. Linter vs. OpenEdge vs. SiteWhere

System Properties Comparison DataFS vs. Ignite vs. Linter vs. OpenEdge vs. SiteWhere

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.

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

RDBMS for high security requirements

Application development environment with integrated database management system

M2M integration platform for persisting/querying time series data

Primary database model

Object oriented DBMS

Key-value store
Relational DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Graph DBMS

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	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

newdatabase.com

ignite.apache.org

linter.ru

www.progress.com/openedge

github.com/sitewhere/sitewhere

Technical documentation

dev.mobiland.com/Overview.xsp

apacheignite.readme.io/docs

documentation.progress.com/output/ua/OpenEdge_latest

sitewhere1.sitewhere.io/index.html

Developer

Mobiland AG

Apache Software Foundation

relex.ru

Progress Software Corporation

SiteWhere

Initial release

2018

2015

1990

1984

2010

Current release

1.1.263, October 2022

Apache Ignite 2.6

OpenEdge 12.2, March 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

C++, Java, .Net

C and C++

Java

Server operating systems

Windows

Linux
OS X
Solaris
Windows

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
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

predefined scheme

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

Secondary indexes

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

close to SQL 92

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

JDBC
ODBC

HTTP REST

Supported programming languages

.Net
C
C#
C++
VB.Net

C#
C++
Java
PHP
Python
Ruby
Scala

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Progress proprietary ABL (Advanced Business Language)

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

Triggers

no, except callback-events from server when changes happened

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding

none

horizontal partitioning

since Version 11.4

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

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

Concurrency

Support for concurrent manipulation of data

yes

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

Users and groups

Users with fine-grained authorization concept

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More resources

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