DBMS > Atos Standard Common Repository vs. ClickHouse vs. IRONdb vs. SWC-DB

System Properties Comparison Atos Standard Common Repository vs. ClickHouse vs. IRONdb vs. SWC-DB

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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.

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

A high performance, scalable Wide Column DBMS

Primary database model

Document store
Key-value store

Relational DBMS

Time Series DBMS

Wide column store

Secondary database models

Time Series DBMS

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

Score	15.88
Rank	#37	Overall
	#22	Relational DBMS

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Website

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

clickhouse.com

www.circonus.com/solutions/time-series-database/

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

clickhouse.com/docs

docs.circonus.com/irondb/category/getting-started

Developer

Atos Convergence Creators

Clickhouse Inc.

Circonus LLC.

Alex Kashirin

Initial release

2016

2017

2020

Current release

1703

v24.6.2.17-stable, July 2024

V0.10.20, January 2018

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

GPL V3

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.

ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

Implementation language

Java

C++

C and C++

C++

Server operating systems

Linux

FreeBSD
Linux
macOS

Linux

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

Typing

predefined data types such as float or date

optional

yes

text, numeric, histograms

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

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language (Circonus Analytics Query Language: CAQL)

SQL-like query language

APIs and other access methods

LDAP

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

HTTP API

Proprietary protocol
Thrift

Supported programming languages

All languages with LDAP bindings

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

C++

Server-side scripts

Stored procedures

yes

yes, in Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

key based and custom

Automatic, metric affinity per node

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

configurable replication factor, datacenter aware

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

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

LDAP bind authentication

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

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