DBMS > 4D vs. Atos Standard Common Repository vs. Citus vs. KairosDB vs. Lovefield

System Properties Comparison 4D vs. Atos Standard Common Repository vs. Citus vs. KairosDB vs. Lovefield

Editorial information provided by DB-Engines

Name

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

Description

Application development environment with integrated database management system

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

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

Distributed Time Series DBMS based on Cassandra or H2

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

www.4d.com

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

www.citusdata.com

github.com/kairosdb/kairosdb

google.github.io/lovefield

Technical documentation

developer.4d.com

docs.citusdata.com

kairosdb.github.io

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

4D, Inc

Atos Convergence Creators

Google

Initial release

1984

2016

2010

2013

2014

Current release

v20, April 2023

1703

8.1, December 2018

1.2.2, November 2018

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

AGPL, commercial license also available

Open Source

Apache 2.0

Open Source

Apache 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

Java

JavaScript

Server operating systems

OS X
Windows

Linux

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

Schema and schema-less with LDAP views

yes

schema-free

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

specific XML type available, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

yes

standard, with numerous extensions

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

LDAP

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

4D proprietary IDE
PHP

All languages with LDAP bindings

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java
JavaScript

Node.js
PHP
Python

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

cell division

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Source-replica replication

other methods possible by using 3rd party extensions

selectable replication factor

based on Cassandra

none

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

Users and groups

LDAP bind authentication

fine grained access rights according to SQL-standard

simple password-based access control

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More resources

DB-Engines blog posts

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