DBMS > 4D vs. AnzoGraph DB vs. Atos Standard Common Repository vs. Databricks

System Properties Comparison 4D vs. AnzoGraph DB vs. Atos Standard Common Repository vs. Databricks

Please select another system to include it in the comparison.

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

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

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

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

Primary database model

Relational DBMS

Graph DBMS
RDF store

Document store
Key-value store

Document store
Relational DBMS

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

Score	2.68
Rank	#110	Overall
	#54	Relational DBMS

Score	0.27
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	76.33
Rank	#17	Overall
	#3	Document stores
	#11	Relational DBMS

Website

www.4d.com

cambridgesemantics.com/anzograph

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

www.databricks.com

Technical documentation

developer.4d.com

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

docs.databricks.com

Developer

4D, Inc

Cambridge Semantics

Atos Convergence Creators

Databricks

Initial release

1984

2018

2016

2013

Current release

v20, April 2023

2.3, January 2021

1703

License

Commercial or Open Source

commercial

free trial version available

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

Server operating systems

OS X
Windows

Linux

hosted

Data scheme

yes

Schema-free and OWL/RDFS-schema support

Schema and schema-less with LDAP views

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

optional

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

SPARQL and SPARQL* as primary query language. Cypher preview.

with Databricks SQL

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

LDAP

JDBC
ODBC
RESTful HTTP API

Supported programming languages

4D proprietary IDE
PHP

C++
Java
Python

All languages with LDAP bindings

Python
R
Scala

Server-side scripts

Stored procedures

yes

user defined functions and aggregates

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

Sharding

cell division

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication in MPP-Cluster

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

not needed in graphs

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

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

Access rights for users and roles

LDAP bind authentication

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

show all

Recent citations in the news

AnzoGraph review: A graph database for deep analytics
15 April 2019, InfoWorld

Cambridge Semantics Unveils AnzoGraph DB with Geospatial Analytics
19 June 2020, Solutions Review

AnzoGraph: A W3C Standards-Based Graph Database | by Jo Stichbury
8 February 2019, Towards Data Science

Back to the future: Does graph database success hang on query language?
5 March 2018, ZDNet

Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access
23 January 2020, Solutions Review

provided by Google News

This Is the Platform Nancy Pelosi Used to Make Her Private Investment in Databricks
12 April 2024, Yahoo Finance

Databricks' New Open Source LLM
8 April 2024, Forbes

AI is Driving Record Sales at Multibillion-Dollar Databricks. An IPO Can Wait … - WSJ
6 March 2024, The Wall Street Journal

Top 5 Lessons Learned from Databricks' Journey from $400M to $1.5B+
23 April 2024, SaaStr

Databricks CEO discusses DBRX, a new LLM
1 April 2024, CNBC

provided by Google News

Share this page