DBMS > Quasardb vs. Riak KV vs. Sadas Engine vs. Trafodion

System Properties Comparison Quasardb vs. Riak KV vs. Sadas Engine vs. Trafodion

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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, high-performance timeseries database

Distributed, fault tolerant key-value store

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Transactional SQL-on-Hadoop DBMS

Primary database model

Time Series DBMS

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	0.19
Rank	#327	Overall
	#30	Time Series DBMS

Score	4.44
Rank	#80	Overall
	#9	Key-value stores

Score	0.03
Rank	#379	Overall
	#156	Relational DBMS

Website

quasar.ai

www.sadasengine.com

trafodion.apache.org

Technical documentation

doc.quasar.ai/master

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

trafodion.apache.org/documentation.html

Developer

quasardb

OpenSource, formerly Basho Technologies

SADAS s.r.l.

Apache Software Foundation, originally developed by HP

Initial release

2009

2006

2014

Current release

3.14.1, January 2024

3.2.0, December 2022

8.0

2.3.0, February 2019

License

Commercial or Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache version 2, commercial enterprise edition

commercial

free trial version available

Open Source

Apache 2.0

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++

Erlang

C++

C++, Java

Server operating systems

BSD
Linux
OS X
Windows

Linux
OS X

AIX
Linux
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

yes

with tags

restricted

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

HTTP API

HTTP API
Native Erlang Interface

JDBC
ODBC
Proprietary protocol

ADO.NET
JDBC
ODBC

Supported programming languages

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

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Erlang

Java Stored Procedures

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

Sharding

no "single point of failure"

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication with selectable replication factor

selectable replication factor

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

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

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

managed by 'Learn by Usage'

User concepts

Access control

Cryptographically strong user authentication and audit trail

yes, using Riak Security

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

fine grained access rights according to SQL-standard

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