DBMS > GridGain vs. TempoIQ vs. Trafodion vs. Valentina Server

System Properties Comparison GridGain vs. TempoIQ vs. Trafodion vs. Valentina Server

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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.

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

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

Transactional SQL-on-Hadoop DBMS

Object-relational database and reports server

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

www.gridgain.com

tempoiq.com (offline)

trafodion.apache.org

www.valentina-db.net

Technical documentation

www.gridgain.com/docs/index.html

trafodion.apache.org/documentation.html

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

GridGain Systems, Inc.

TempoIQ

Apache Software Foundation, originally developed by HP

Paradigma Software

Initial release

2007

2012

2014

1999

Current release

GridGain 8.5.1

2.3.0, February 2019

5.7.5

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java, C++, .Net

C++, Java

Server operating systems

Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

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

yes

APIs and other access methods

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

HTTP API

ADO.NET
JDBC
ODBC

ODBC

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C#
Java
JavaScript

Node.js
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

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

Java Stored Procedures

yes

Triggers

yes (cache interceptors and events)

yes

Realtime Alerts

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

via user defined functions and HBase

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

Security Hooks for custom implementations

simple authentication-based access control

fine grained access rights according to SQL-standard

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More resources

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