DBMS > 4D vs. Atos Standard Common Repository vs. Bangdb vs. Lovefield vs. SQLite

System Properties Comparison 4D vs. Atos Standard Common Repository vs. Bangdb vs. Lovefield vs. SQLite

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

Converged and high performance database for device data, events, time series, document and graph

Embeddable relational database for web apps written in pure JavaScript

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Document store
Key-value store

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

www.4d.com

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

bangdb.com

google.github.io/lovefield

www.sqlite.org

Technical documentation

developer.4d.com

docs.bangdb.com

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

www.sqlite.org/docs.html

Developer

4D, Inc

Atos Convergence Creators

Sachin Sinha, BangDB

Google

Dwayne Richard Hipp

Initial release

1984

2016

2012

2014

2000

Current release

v20, April 2023

1703

BangDB 2.0, October 2021

2.1.12, February 2017

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

BSD 3

Open Source

Apache 2.0

Open Source

Public Domain

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, C++

JavaScript

Server operating systems

OS X
Windows

Linux

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

tested with Chrome, Firefox, IE, Safari

server-less

Data scheme

yes

Schema and schema-less with LDAP views

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

optional

yes: string, long, double, int, geospatial, stream, events

yes

not rigid because of 'dynamic typing' concept.

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

yes

close to SQL 92

SQL like support with command line tool

SQL-like query language

via JavaScript builder pattern

yes

SQL-92 is not fully supported

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

LDAP

Proprietary protocol
RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

4D proprietary IDE
PHP

All languages with LDAP bindings

C
C#
C++
Java
Python

JavaScript

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Triggers

yes

yes, Notifications (with Streaming only)

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

cell division

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

selectable replication factor, Knob for CAP (enterprise version only)

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

Tunable consistency, set CAP knob accordingly

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

yes, optimistic concurrency control

yes

via file-system locks

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

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

yes

In-memory capabilities

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

yes

yes, run db with in-memory only mode

yes

using MemoryDB

yes

User concepts

Access control

Users and groups

LDAP bind authentication

yes (enterprise version only)

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