DBMS > Quasardb vs. RethinkDB vs. Riak KV vs. SiriDB vs. SiteWhere

System Properties Comparison Quasardb vs. RethinkDB vs. Riak KV vs. SiriDB vs. SiteWhere

Editorial information provided by DB-Engines

Name

Description

Distributed, high-performance timeseries database

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Distributed, fault tolerant key-value store

Open Source Time Series DBMS

M2M integration platform for persisting/querying time series data

Primary database model

Time Series DBMS

Document store

Key-value store

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

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

quasar.ai

rethinkdb.com

siridb.com

github.com/sitewhere/sitewhere

Technical documentation

doc.quasar.ai/master

rethinkdb.com/docs

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

docs.siridb.com

sitewhere1.sitewhere.io/index.html

Developer

quasardb

The Linux Foundation

since July 2017

OpenSource, formerly Basho Technologies

Cesbit

SiteWhere

Initial release

2009

2017

2010

Current release

3.14.1, January 2024

2.4.1, August 2020

3.2.0, December 2022

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

Open Source

Apache version 2, commercial enterprise edition

Open Source

MIT License

Open Source

Common Public Attribution License Version 1.0

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

Java

Server operating systems

BSD
Linux
OS X
Windows

Linux
OS X
Windows

Linux
OS X

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

predefined scheme

Typing

predefined data types such as float or date

yes

integer and binary

yes

string, binary, float, bool, date, geometry

yes

Numeric data

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

restricted

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

HTTP API

HTTP API
Native Erlang Interface

HTTP API

HTTP REST

Supported programming languages

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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

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

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

Server-side scripts

Stored procedures

Erlang

Triggers

Client-side triggers through changefeeds

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

Sharding

range based

Sharding

no "single point of failure"

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication with selectable replication factor

Source-replica replication

selectable replication factor

yes

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

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

Transaction concepts

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

ACID

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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

Cryptographically strong user authentication and audit trail

yes

users and table-level permissions

yes, using Riak Security

simple rights management via user accounts

Users with fine-grained authorization concept

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