DBMS > Apache Druid vs. Atos Standard Common Repository vs. mSQL vs. OpenTSDB

System Properties Comparison Apache Druid vs. Atos Standard Common Repository vs. mSQL vs. OpenTSDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

mSQL (Mini SQL) is a simple and lightweight RDBMS

Scalable Time Series DBMS based on HBase

Primary database model

Relational DBMS
Time Series DBMS

Document store
Key-value store

Relational DBMS

Time Series DBMS

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

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	1.26
Rank	#163	Overall
	#74	Relational DBMS

Score	1.59
Rank	#140	Overall
	#12	Time Series DBMS

Website

druid.apache.org

atos.net/en/convergence-creators/portfolio/standard-common-repository

hughestech.com.au/products/msql

opentsdb.net

Technical documentation

druid.apache.org/docs/latest/design

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

Developer

Apache Software Foundation and contributors

Atos Convergence Creators

Hughes Technologies

currently maintained by Yahoo and other contributors

Initial release

2012

2016

1994

2011

Current release

30.0.0, June 2024

1703

4.4, October 2021

License

Commercial or Open Source

Open Source

Apache license v2

commercial

free licenses can be provided

Open Source

LGPL

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

Server operating systems

Linux
OS X
Unix

Linux

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

Linux
Windows

Data scheme

yes

schema-less columns are supported

Schema and schema-less with LDAP views

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

yes

numeric data for metrics, strings for tags

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

SQL

Support of SQL

SQL for querying

A subset of ANSI SQL is implemented

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

APIs and other access methods

JDBC
RESTful HTTP/JSON API

LDAP

JDBC
ODBC

HTTP API
Telnet API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

All languages with LDAP bindings

C
C++
Delphi
Java
Perl
PHP
Tcl

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

cell division

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

none

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

LDAP bind authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

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

show all

Recent citations in the news

Apache® Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers’ Choice Awards
26 January 2024, Business Wire

Imply Announces the Availability of Imply Polaris, a Database-as-a-Service Built from Apache Druid, on Microsoft Azure
26 June 2024, Yahoo Finance

'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers
21 February 2024, Dark Reading

Apache Druid Takes Its Place In The Pantheon Of Databases
16 June 2022, The Next Platform

How to connect DataGrip to Apache Druid
18 October 2021, Towards Data Science

provided by Google News

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

LogicMonitor Rolls a Time Series Database for Finer-Grain Reporting
1 June 2016, The New Stack

A real-time processing revival
1 April 2015, O'Reilly Media

provided by Google News

Share this page