DBMS > Quasardb vs. ReductStore vs. STSdb vs. Trafodion

System Properties Comparison Quasardb vs. ReductStore vs. STSdb 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

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Transactional SQL-on-Hadoop DBMS

Primary database model

Time Series DBMS

Key-value store

Relational DBMS

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

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

quasar.ai

github.com/reductstore
www.reduct.store

github.com/STSSoft/STSdb4

trafodion.apache.org

Technical documentation

doc.quasar.ai/master

www.reduct.store/docs

trafodion.apache.org/documentation.html

Developer

quasardb

ReductStore LLC

STS Soft SC

Apache Software Foundation, originally developed by HP

Initial release

2009

2023

2011

2014

Current release

3.14.1, January 2024

1.9, March 2024

4.0.8, September 2015

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

Business Source License 1.1

Open Source

GPLv2, commercial license 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++

C++, Rust

C++, Java

Server operating systems

BSD
Linux
OS X
Windows

Docker
Linux
macOS
Windows

Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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.

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

HTTP API

.NET Client API

ADO.NET
JDBC
ODBC

Supported programming languages

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

C++
JavaScript (Node.js)
Python
Rust

C#
Java

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication with 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

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

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

User concepts

Access control

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

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