DBMS > GBase vs. GigaSpaces vs. MySQL vs. TypeDB vs. WakandaDB

System Properties Comparison GBase vs. GigaSpaces vs. MySQL vs. TypeDB 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.

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

Widely used open source RDBMS

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

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

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Key/Value like access via memcached API

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Object oriented DBMS

Secondary database models

Graph DBMS
Search engine

Document store
Spatial DBMS

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.65
Rank	#234	Overall
	#20	Graph DBMS
	#107	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

Technical documentation

docs.gigaspaces.com/latest/landing.html

dev.mysql.com/doc

typedb.com/docs

wakanda.github.io/doc

Developer

General Data Technology Co., Ltd.

Gigaspaces Technologies

Oracle

since 2010, originally MySQL AB, then Sun

Vaticle

Wakanda SAS

Initial release

2004

2000

1995

2016

2012

Current release

GBase 8a, GBase 8s, GBase 8c

15.5, September 2020

8.4.0, April 2024

2.26.3, January 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; Commercial licenses available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL Version 3, commercial licenses available

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

Java, C++, .Net

C and C++

Java

C++, JavaScript

Server operating systems

Linux

Linux
macOS
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

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.

yes

XML can be used for describing objects metadata

yes

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

SQL-99 for query and DML statements

yes

with proprietary extensions

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

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

ADO.NET
JDBC
ODBC
Proprietary native API

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

RESTful HTTP API

Supported programming languages

.Net
C++
Java
Python
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

JavaScript

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax

yes

Triggers

yes

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

by using Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication
Source-replica replication

Multi-source replication

by using Cassandra

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

substituted by the relationship feature

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

yes

Role-based access control

Users with fine-grained authorization concept

no user groups or roles

yes

at REST API level; other APIs in progress

yes

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Licensing and pricing models

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