DBMS > 4D vs. Atos Standard Common Repository vs. BaseX vs. Google BigQuery vs. RavenDB

System Properties Comparison 4D vs. Atos Standard Common Repository vs. BaseX vs. Google BigQuery vs. RavenDB

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

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

Large scale data warehouse service with append-only tables

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Relational DBMS

Document store
Key-value store

Native XML DBMS

Relational DBMS

Document store

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Website

www.4d.com

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

basex.org

cloud.google.com/bigquery

ravendb.net

Technical documentation

developer.4d.com

docs.basex.org

cloud.google.com/bigquery/docs

ravendb.net/docs

Developer

4D, Inc

Atos Convergence Creators

BaseX GmbH

Google

Hibernating Rhinos

Initial release

1984

2016

2007

2010

Current release

v20, April 2023

1703

10.7, August 2023

5.4, July 2022

License

Commercial or Open Source

commercial

Open Source

BSD license

commercial

Open Source

AGPL version 3, commercial license available

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

Server operating systems

OS X
Windows

Linux

Linux
OS X
Windows

hosted

Linux
macOS
Raspberry Pi
Windows

Data scheme

yes

Schema and schema-less with LDAP views

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

XQuery supports types

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

yes

close to SQL 92

yes

SQL-like query language (RQL)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

LDAP

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

RESTful HTTP/JSON API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

4D proprietary IDE
PHP

All languages with LDAP bindings

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

cell division

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

multiple readers, single writer

Since BigQuery is designed for querying data

ACID, Cluster-wide transaction available

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

Users and groups

LDAP bind authentication

Users with fine-grained authorization concept on 4 levels

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Authorization levels configured per client per database

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