DBMS > GridGain vs. RDFox vs. TempoIQ vs. Yanza

System Properties Comparison GridGain vs. RDFox vs. TempoIQ vs. Yanza

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

High performance knowledge graph and semantic reasoning engine

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Time Series DBMS for IoT Applications

Primary database model

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Graph DBMS
RDF store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	0.22
Rank	#305	Overall
	#25	Graph DBMS
	#15	RDF stores

Website

www.gridgain.com

www.oxfordsemantic.tech

tempoiq.com (offline)

yanza.com

Technical documentation

www.gridgain.com/docs/index.html

docs.oxfordsemantic.tech

Developer

GridGain Systems, Inc.

Oxford Semantic Technologies

TempoIQ

Yanza

Initial release

2007

2017

2012

2015

Current release

GridGain 8.5.1

6.0, Septermber 2022

License

Commercial or Open Source

commercial, open source

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, C++, .Net, Python, REST, SQL

C++

Server operating systems

Linux
OS X
Solaris
Windows
z/OS

Linux
macOS
Windows

Windows

Data scheme

yes

RDF schemas

schema-free

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

APIs and other access methods

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

RESTful HTTP API
SPARQL 1.1

HTTP API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C
Java

C#
Java
JavaScript

Node.js
Python
Ruby

any language that supports HTTP calls

Server-side scripts

Stored procedures

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

Triggers

yes (cache interceptors and events)

yes

Realtime Alerts

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

replication via a shared file system

none

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

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Immediate Consistency

Foreign keys

Referential integrity

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

Role-based access control
Security Hooks for custom implementations

Roles, resources, and access types

simple authentication-based access control

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More resources

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