DBMS > Kingbase vs. Splice Machine vs. Trafodion vs. WakandaDB

System Properties Comparison Kingbase vs. Splice Machine vs. Trafodion vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Transactional SQL-on-Hadoop DBMS

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

Object oriented DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

Technical documentation

splicemachine.com/how-it-works

trafodion.apache.org/documentation.html

wakanda.github.io/doc

Developer

BeiJing KINGBASE Information technologies inc.

Splice Machine

Apache Software Foundation, originally developed by HP

Wakanda SAS

Initial release

1999

2014

2012

Current release

V8.0, August 2021

3.1, March 2021

2.3.0, February 2019

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

AGPL 3.0, commercial license available

Open Source

Apache 2.0

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.

Implementation language

C and Java

Java

C++, Java

C++, JavaScript

Server operating systems

Linux
Windows

Linux
OS X
Solaris
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

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

yes

APIs and other access methods

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

JDBC
Native Spark Datasource
ODBC

ADO.NET
JDBC
ODBC

RESTful HTTP API

Supported programming languages

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

All languages supporting JDBC/ODBC/ADO.Net

JavaScript

Server-side scripts

Stored procedures

user defined functions

yes

Java

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes, via HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

yes

via user defined functions and HBase

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

yes, multi-version concurrency control (MVCC)

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

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

fine grained access rights according to SQL-standard

yes

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