DBMS > 4D vs. Atos Standard Common Repository vs. BaseX vs. HEAVY.AI vs. HugeGraph

System Properties Comparison 4D vs. Atos Standard Common Repository vs. BaseX vs. HEAVY.AI vs. HugeGraph

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.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

A fast-speed and highly-scalable Graph DBMS

Primary database model

Relational DBMS

Document store
Key-value store

Native XML DBMS

Relational DBMS

Graph 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	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Website

www.4d.com

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

basex.org

github.com/heavyai/heavydb
www.heavy.ai

github.com/hugegraph
hugegraph.apache.org

Technical documentation

developer.4d.com

docs.basex.org

docs.heavy.ai

hugegraph.apache.org/docs

Developer

4D, Inc

Atos Convergence Creators

BaseX GmbH

HEAVY.AI, Inc.

Baidu

Initial release

1984

2016

2007

2016

2018

Current release

v20, April 2023

1703

10.7, August 2023

5.10, January 2022

0.9

License

Commercial or Open Source

commercial

Open Source

BSD license

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache Version 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

C++ and CUDA

Java

Server operating systems

OS X
Windows

Linux

Linux
OS X
Windows

Linux

Linux
macOS
Unix

Data scheme

yes

Schema and schema-less with LDAP views

schema-free

yes

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

also supports composite index and range index

SQL

Support of SQL

yes

close to SQL 92

yes

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

JDBC
ODBC
Thrift
Vega

Java API
RESTful HTTP API
TinkerPop Gremlin

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

All languages supporting JDBC/ODBC/Thrift
Python

Groovy
Java
Python

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

Triggers

yes

via events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

cell division

none

Sharding

Round robin

yes

depending on used storage backend, e.g. Cassandra and HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

none

Multi-source replication

yes

depending on used storage backend, e.g. Cassandra and HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

ACID

Atomic execution of specific operations

multiple readers, single writer

ACID

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

fine grained access rights according to SQL-standard

Users, roles and permissions

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