DBMS > Infobright vs. openGauss vs. RavenDB vs. TinkerGraph

System Properties Comparison Infobright vs. openGauss vs. RavenDB vs. TinkerGraph

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

Open Source Operational and Transactional Enterprise NoSQL Document Database

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Relational DBMS

Document store

Graph DBMS

Secondary database models

Document store
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	1.08
Rank	#183	Overall
	#84	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

ignitetech.com/softwarelibrary/infobrightdb

gitee.com/opengauss
opengauss.org

ravendb.net

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

docs.opengauss.org/en
gitee.com/opengauss/docs

ravendb.net/docs

Developer

Ignite Technologies Inc.; formerly InfoBright Inc.

Huawei and openGauss community

Hibernating Rhinos

Initial release

2005

2019

2010

2009

Current release

3.0, March 2022

5.4, July 2022

License

Commercial or Open Source

commercial

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

Open Source

AGPL version 3, commercial license available

Open Source

Apache 2.0

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

C, C++, Java

Java

Server operating systems

Linux
Windows

Linux

Linux
macOS
Raspberry Pi
Windows

Data scheme

yes

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.

Secondary indexes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

ANSI SQL 2011

SQL-like query language (RQL)

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

TinkerPop 3

Supported programming languages

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

C
C++
Java

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Groovy
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash)

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional

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

Access rights for users, groups and roles according to SQL-standard

Authorization levels configured per client per database

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

openGauss Open Source Community Officially Launch
1 July 2020, Huawei

The openGauss powers database industry forward through innovation
6 January 2022, Global Times

provided by Google News

RavenDB Welcomes David Baruc as Chief Revenue Officer: Seasoned Tech Leader to Drive Global Sales and ...
13 June 2023, PR Newswire

Install the NoSQL RavenDB Data System
14 May 2021, The New Stack

Oren Eini on RavenDB, Including Consistency Guarantees and C# as the Implementation Language
23 May 2022, InfoQ.com

RavenDB Adds Graph Queries
15 May 2019, Datanami

How I Created a RavenDB Python Client
23 September 2016, Visual Studio Magazine

provided by Google News

Automated testing of Amazon Neptune data access with Apache TinkerPop Gremlin | Amazon Web Services
28 September 2022, AWS Blog

Simple Deployment of a Graph Database: JanusGraph | by Edward Elson Kosasih
12 October 2020, Towards Data Science

Why developers like Apache TinkerPop, an open source framework for graph computing | Amazon Web Services
27 September 2021, AWS Blog

InfiniteGraph Gets Support for Common Graph Database Language and More
21 February 2012, SiliconANGLE News

Introducing Gremlin query hints for Amazon Neptune | AWS Database Blog
26 February 2019, AWS Blog

provided by Google News

Share this page