DBMS > Apache Druid vs. Atos Standard Common Repository vs. Datomic vs. MySQL

System Properties Comparison Apache Druid vs. Atos Standard Common Repository vs. Datomic vs. MySQL

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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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Widely used open source RDBMS

Primary database model

Relational DBMS
Time Series DBMS

Document store
Key-value store

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Website

druid.apache.org

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

www.datomic.com

www.mysql.com

Technical documentation

druid.apache.org/docs/latest/design

docs.datomic.com

dev.mysql.com/doc

Developer

Apache Software Foundation and contributors

Atos Convergence Creators

Cognitect

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2012

2016

2012

1995

Current release

29.0.1, April 2024

1703

1.0.6735, June 2023

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache license v2

commercial

limited edition free

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

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Implementation language

Java

Java, Clojure

C and C++

Server operating systems

Linux
OS X
Unix

Linux

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-less columns are supported

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

yes

optional

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

SQL

Support of SQL

SQL for querying

yes

with proprietary extensions

APIs and other access methods

JDBC
RESTful HTTP/JSON API

LDAP

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

All languages with LDAP bindings

Clojure
Java

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

proprietary syntax

Triggers

yes

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

cell division

none

But extensive use of caching in the application peers

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

none

But extensive use of caching in the application peers

Multi-source replication
Source-replica replication

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

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic execution of specific operations

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

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

Users with fine-grained authorization concept

no user groups or roles

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