DBMS > mSQL vs. ReductStore vs. Riak TS vs. Sphinx vs. Tkrzw

System Properties Comparison mSQL vs. ReductStore vs. Riak TS vs. Sphinx vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

mSQL (Mini SQL) is a simple and lightweight RDBMS

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.

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Open source search engine for searching in data from different sources, e.g. relational databases

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

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

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

hughestech.com.au/products/msql

github.com/reductstore
www.reduct.store

sphinxsearch.com

dbmx.net/tkrzw

Technical documentation

www.reduct.store/docs

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

sphinxsearch.com/docs

Developer

Hughes Technologies

ReductStore LLC

Open Source, formerly Basho Technologies

Sphinx Technologies Inc.

Mikio Hirabayashi

Initial release

1994

2023

2015

2001

2020

Current release

4.4, October 2021

1.9, March 2024

3.0.0, September 2022

3.5.1, February 2023

0.9.3, August 2020

License

Commercial or Open Source

commercial

free licenses can be provided

Open Source

Business Source License 1.1

Open Source

GPL version 2, commercial licence available

Open Source

Apache Version 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++, Rust

Erlang

C++

Server operating systems

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Docker
Linux
macOS
Windows

Linux
OS X

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
macOS

Data scheme

yes

schema-free

yes

schema-free

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

yes

restricted

yes

full-text index on all search fields

SQL

Support of SQL

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes, limited

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
ODBC

HTTP API

HTTP API
Native Erlang Interface

Proprietary protocol

Supported programming languages

C
C++
Delphi
Java
Perl
PHP
Tcl

C++
JavaScript (Node.js)
Python
Rust

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++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

yes

In-memory capabilities

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

yes

using specific database classes

User concepts

Access control

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More resources

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