DBMS > GigaSpaces vs. Infobright vs. OrigoDB vs. TigerGraph

System Properties Comparison GigaSpaces vs. Infobright vs. OrigoDB vs. TigerGraph

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

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

A fully ACID in-memory object graph database

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

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Document store
Object oriented DBMS

Graph DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	0.91
Rank	#197	Overall
	#33	Document stores
	#7	Object oriented DBMS

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Score	0.00
Rank	#385	Overall
	#54	Document stores
	#21	Object oriented DBMS

Score	1.44
Rank	#152	Overall
	#14	Graph DBMS

Website

www.gigaspaces.com

ignitetech.com/softwarelibrary/infobrightdb

origodb.com

www.tigergraph.com

Technical documentation

docs.gigaspaces.com/latest/landing.html

origodb.com/docs

docs.tigergraph.com

Developer

Gigaspaces Technologies

Ignite Technologies Inc.; formerly InfoBright Inc.

Robert Friberg et al

Initial release

2000

2005

2009

under the name LiveDB

2017

Current release

15.5, September 2020

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

commercial

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

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

C++

Server operating systems

Linux
macOS
Solaris
Windows

Linux
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

XML can be used for describing objects metadata

can be achieved using .NET

Secondary indexes

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

SQL-like query language (GSQL)

APIs and other access methods

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC

.NET Client API
HTTP API
LINQ

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

Supported programming languages

.Net
C++
Java
Python
Scala

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

.Net

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

yes, event driven architecture

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

depending on model

yes

Relationships in graphs

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

Write ahead log

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

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Role based authorization

Role-based access control

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Lyvia Group Partners with GigaSpaces to Accelerate Digital Innovation in European Enterprises
24 October 2023, Cision News

GigaSpaces to hand out almost $14 million in dividends following Cloudify’s acquisition by Dell
19 July 2023, CTech

GigaSpaces Announces Version 16.0 with Breakthrough Data Integration Tools to Ease Enterprises' Digital Transformation Challenges
3 November 2021, PR Newswire

Your occasional storage digest with GigaSpaces, Virtana and NAND ship data
7 December 2020, Blocks & Files

GigaSpaces Plans Spinoff of Cloudify Division to Focus on Enterprise Hybrid Cloud Management and Network Or...
27 July 2017, DevOps.com

provided by Google News

TigerGraph Unveils CoPilot, Version 4.0, and New CEO
30 April 2024, Datanami

TigerGraph unveils GenAI assistant, introduces new CEO
30 April 2024, TechTarget

How TigerGraph CoPilot enables graph-augmented AI
30 April 2024, InfoWorld

graph database Archives
26 June 2024, insideBIGDATA

TigerGraph Bolsters DB for Enterprise Graph Workloads
1 November 2023, Datanami

provided by Google News

Share this page