DBMS > AgensGraph vs. Databend vs. GBase vs. Infobright

System Properties Comparison AgensGraph vs. Databend vs. GBase vs. Infobright

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Website

bitnine.net/agensgraph

github.com/datafuselabs/databend
www.databend.com

www.gbase.cn

ignitetech.com/softwarelibrary/infobrightdb

Technical documentation

bitnine.net/documentation

docs.databend.com

Developer

Bitnine Global Inc.

Databend Labs

General Data Technology Co., Ltd.

Ignite Technologies Inc.; formerly InfoBright Inc.

Initial release

2016

2021

2004

2005

Current release

2.1, December 2018

1.0.59, April 2023

GBase 8a, GBase 8s, GBase 8c

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache Version 2.0

commercial

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

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

Rust

C, Java, Python

Server operating systems

Linux
OS X
Windows

hosted
Linux
macOS

Linux

Linux
Windows

Data scheme

depending on used data model

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

Knowledge Grid Technology used instead

SQL

Support of SQL

yes

Standard with numerous extensions

yes

APIs and other access methods

Cypher Query Language
JDBC

CLI Client
JDBC
RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

Go
Java
JavaScript (Node.js)
Python
Rust

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

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

none

horizontal partitioning (by range, list and hash) and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles

yes

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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