DBMS > OpenQM vs. Quasardb vs. SWC-DB vs. Yaacomo

System Properties Comparison OpenQM vs. Quasardb vs. SWC-DB vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

QpenQM is a high-performance, self-tuning, multi-value DBMS

Distributed, high-performance timeseries database

A high performance, scalable Wide Column DBMS

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

quasar.ai

github.com/kashirin-alex/swc-db
www.swcdb.org

yaacomo.com

Technical documentation

doc.quasar.ai/master

Developer

Rocket Software, originally Martin Phillips

quasardb

Alex Kashirin

Q2WEB GmbH

Initial release

1993

2009

2020

2009

Current release

3.4-12

3.14.1, January 2024

0.5, April 2021

License

Commercial or Open Source

Open Source

GPLv2, extended commercial license available

commercial

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

Open Source

GPL V3

commercial

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++

Server operating systems

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

BSD
Linux
OS X
Windows

Linux

Android
Linux
Windows

Data scheme

yes

with some exceptions

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.

yes

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

HTTP API

Proprietary protocol
Thrift

JDBC
ODBC

Supported programming languages

.Net
Basic
C
Java
Objective C
PHP
Python

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

C++

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

consistent hashing

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication with selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

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

yes

User concepts

Access control

Access rights can be defined down to the item level

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

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