DBMS > DataFS vs. GridGain vs. InterSystems IRIS

System Properties Comparison DataFS vs. GridGain vs. InterSystems IRIS

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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.

GridGain is an in-memory computing platform, built on Apache Ignite

A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability

Primary database model

Object oriented DBMS

Key-value store
Relational DBMS

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Secondary database models

Graph DBMS

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

Score	0.07
Rank	#362	Overall
	#17	Object oriented DBMS

Score	1.53
Rank	#155	Overall
	#26	Key-value stores
	#73	Relational DBMS

Score	4.39
Rank	#81	Overall
	#13	Document stores
	#10	Key-value stores
	#1	Object oriented DBMS
	#44	Relational DBMS

Website

newdatabase.com

www.gridgain.com

www.intersystems.com/products/intersystems-iris

Technical documentation

dev.mobiland.com/Overview.xsp

www.gridgain.com/docs/index.html

docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls

Developer

Mobiland AG

GridGain Systems, Inc.

InterSystems

Initial release

2018

2007

2018

Current release

1.1.263, October 2022

GridGain 8.5.1

2023.3, June 2023

License

Commercial or Open Source

commercial

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, C++, .Net

Server operating systems

Windows

Linux
OS X
Solaris
Windows

AIX
Linux
macOS
Ubuntu
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

depending on used data model

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

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

JDBC
ODBC
RESTful HTTP API

Supported programming languages

.Net
C
C#
C++
VB.Net

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

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

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Source-replica replication

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

yes

More information provided by the system vendor

Specific characteristics

InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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More resources

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