DBMS > Riak KV vs. Trafodion vs. Transbase vs. VoltDB

System Properties Comparison Riak KV vs. Trafodion vs. Transbase vs. VoltDB

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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

Distributed, fault tolerant key-value store

Transactional SQL-on-Hadoop DBMS

A resource-optimized, high-performance, universally applicable RDBMS

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

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

Score	3.84
Rank	#76	Overall
	#9	Key-value stores

Score	0.05
Rank	#355	Overall
	#150	Relational DBMS

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Website

trafodion.apache.org

www.transaction.de/en/products/transbase.html

www.voltdb.com

Technical documentation

www.tiot.jp/riak-docs/riak/kv/latest

trafodion.apache.org/documentation.html

www.transaction.de/en/products/transbase/features.html

docs.voltdb.com

Developer

OpenSource, formerly Basho Technologies

Apache Software Foundation, originally developed by HP

Transaction Software GmbH

VoltDB Inc.

Initial release

2009

2014

1987

2010

Current release

3.2.0, December 2022

2.3.0, February 2019

Transbase 8.3, 2022

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache version 2, commercial enterprise edition

Open Source

Apache 2.0

commercial

free development license

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

C++, Java

C and C++

Java, C++

Server operating systems

Linux
OS X

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Linux
OS X

for development

Data scheme

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

HTTP API
Native Erlang Interface

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Erlang

Java Stored Procedures

yes

Java

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes, via HBase

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

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

User concepts

Access control

yes, using Riak Security

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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More resources

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