DBMS > 4D vs. Atos Standard Common Repository vs. Bangdb vs. Google Cloud Spanner

System Properties Comparison 4D vs. Atos Standard Common Repository vs. Bangdb vs. Google Cloud Spanner

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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

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

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

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	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Website

www.4d.com

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

bangdb.com

cloud.google.com/spanner

Technical documentation

developer.4d.com

docs.bangdb.com

cloud.google.com/spanner/docs

Developer

4D, Inc

Atos Convergence Creators

Sachin Sinha, BangDB

Google

Initial release

1984

2016

2012

2017

Current release

v20, April 2023

1703

BangDB 2.0, October 2021

License

Commercial or Open Source

commercial

Open Source

BSD 3

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C, C++

Server operating systems

OS X
Windows

Linux

hosted

Data scheme

yes

Schema and schema-less with LDAP views

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

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

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

yes

close to SQL 92

SQL like support with command line tool

yes

Query statements complying to ANSI 2011

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

LDAP

Proprietary protocol
RESTful HTTP API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

Supported programming languages

4D proprietary IDE
PHP

All languages with LDAP bindings

C
C#
C++
Java
Python

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

yes, Notifications (with Streaming only)

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

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

Multi-source replication with 3 replicas for regional instances.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

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

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Strict serializable isolation

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

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

User concepts

Access control

Users and groups

LDAP bind authentication

yes (enterprise version only)

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources

DB-Engines blog posts

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