DBMS > GBase vs. Graph Engine vs. PostgreSQL vs. TigerGraph vs. WakandaDB

System Properties Comparison GBase vs. Graph Engine vs. PostgreSQL vs. TigerGraph vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

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

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Graph DBMS

Object oriented DBMS

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

Technical documentation

www.graphengine.io/docs/manual

www.postgresql.org/docs

docs.tigergraph.com

wakanda.github.io/doc

Developer

General Data Technology Co., Ltd.

Microsoft

PostgreSQL Global Development Group

www.postgresql.org/developer

Wakanda SAS

Initial release

2004

2010

1989

1989: Postgres, 1996: PostgreSQL

2017

2012

Current release

GBase 8a, GBase 8s, GBase 8c

16.3, May 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

BSD

commercial

Open Source

AGPLv3, extended commercial license available

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.

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Implementation language

C, Java, Python

.NET and C

C++

C++, JavaScript

Server operating systems

Linux

.NET

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Linux

Linux
OS X
Windows

Data scheme

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

yes

standard with numerous extensions

SQL-like query language (GSQL)

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

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

RESTful HTTP API

Supported programming languages

C#
C++
F#
Visual Basic

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++
Java

JavaScript

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning

partitioning by range, list and (since PostgreSQL 11) by hash

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

other methods possible by using 3rd party extensions

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

yes

fine grained access rights according to SQL-standard

Role-based access control

yes

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.

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