DBMS > Infobright vs. Oracle Coherence vs. TigerGraph vs. TimesTen

System Properties Comparison Infobright vs. Oracle Coherence vs. TigerGraph vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

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

Oracles in-memory data grid solution

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

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

Score	0.86
Rank	#201	Overall
	#96	Relational DBMS

Score	1.81
Rank	#128	Overall
	#22	Key-value stores

Score	1.40
Rank	#152	Overall
	#14	Graph DBMS

Score	1.23
Rank	#163	Overall
	#74	Relational DBMS

Website

ignitetech.com/softwarelibrary/infobrightdb

www.oracle.com/java/coherence

www.tigergraph.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.oracle.com/en/middleware/standalone/coherence

docs.tigergraph.com

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Ignite Technologies Inc.; formerly InfoBright Inc.

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2005

2007

2017

1998

Current release

14.1, August 2023

Release 22.1

License

Commercial or Open Source

commercial

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

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++

Server operating systems

Linux
Windows

All OS with a Java VM

Linux

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

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.

Secondary indexes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

SQL-like query language (GSQL)

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

JCache
JPA
RESTful HTTP API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

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

.Net
C++
Java

C++
Java

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

yes

PL/SQL

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, with selectable consistency level

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

yes

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

authentification to access the cache via certificates or http basic authentication

Role-based access control

fine grained access rights according to SQL-standard

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