DBMS > OpenTSDB vs. ReductStore vs. Sadas Engine vs. Sphinx

System Properties Comparison OpenTSDB vs. ReductStore vs. Sadas Engine vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

Scalable Time Series DBMS based on HBase

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.

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

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

Primary database model

Time Series DBMS

Relational DBMS

Search engine

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

Score	1.59
Rank	#140	Overall
	#12	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Website

opentsdb.net

github.com/reductstore
www.reduct.store

www.sadasengine.com

sphinxsearch.com

Technical documentation

opentsdb.net/docs/build/html/index.html

www.reduct.store/docs

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

sphinxsearch.com/docs

Developer

currently maintained by Yahoo and other contributors

ReductStore LLC

SADAS s.r.l.

Sphinx Technologies Inc.

Initial release

2011

2023

2006

2001

Current release

1.9, March 2024

8.0

3.5.1, February 2023

License

Commercial or Open Source

Open Source

LGPL

Open Source

Business Source License 1.1

commercial

free trial version available

Open Source

GPL version 2, commercial licence available

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

Java

C++, Rust

C++

Server operating systems

Linux
Windows

Docker
Linux
macOS
Windows

AIX
Linux
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

numeric data for metrics, strings for tags

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

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

APIs and other access methods

HTTP API
Telnet API

HTTP API

JDBC
ODBC
Proprietary protocol

Proprietary protocol

Supported programming languages

Erlang
Go
Java
Python
R
Ruby

C++
JavaScript (Node.js)
Python
Rust

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

horizontal partitioning

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Immediate Consistency

Foreign keys

Referential integrity

yes

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.

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

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

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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Recent citations in the news

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10 February 2022, hackernoon.com

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1 June 2016, The New Stack

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