DBMS > Greenplum vs. STSdb vs. TDSQL for MySQL vs. WakandaDB

System Properties Comparison Greenplum vs. STSdb vs. TDSQL for MySQL vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

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

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	0.85
Rank	#207	Overall
	#97	Relational DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

greenplum.org

github.com/STSSoft/STSdb4

www.tencentcloud.com/products/dcdb

wakanda.github.io

Technical documentation

docs.greenplum.org

www.tencentcloud.com/document/product/1042

wakanda.github.io/doc

Developer

Pivotal Software Inc.

STS Soft SC

Tencent

Wakanda SAS

Initial release

2005

2011

2013

2012

Current release

7.0.0, September 2023

4.0.8, September 2015

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

commercial

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, JavaScript

Server operating systems

Linux

Windows

hosted

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

since Version 4.2

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC

.NET Client API

JDBC
ODBC

RESTful HTTP API

Supported programming languages

C
Java
Perl
Python
R

C#
Java

C
C#
C++
Java
PHP
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication
Source-replica 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

Foreign keys

Referential integrity

yes

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

yes

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More resources

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