DBMS > 4D vs. FatDB vs. Hive vs. JanusGraph vs. Trafodion

System Properties Comparison 4D vs. FatDB vs. Hive vs. JanusGraph vs. Trafodion

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Application development environment with integrated database management system

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Graph DBMS

Relational DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Website

Technical documentation

developer.4d.com

cwiki.apache.org/confluence/display/Hive/Home

docs.janusgraph.org

trafodion.apache.org/documentation.html

Developer

4D, Inc

FatCloud

Apache Software Foundation

initially developed by Facebook

Linux Foundation; originally developed as Titan by Aurelius

Apache Software Foundation, originally developed by HP

Initial release

1984

2012

2017

2014

Current release

v20, April 2023

3.1.3, April 2022

0.6.3, February 2023

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Apache 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++, Java

Server operating systems

OS X
Windows

Windows

All OS with a Java VM

Linux
OS X
Unix
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

Via inetgration in SQL Server

SQL-like DML and DDL statements

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JDBC
ODBC
Thrift

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
ODBC

Supported programming languages

4D proprietary IDE
PHP

C++
Java
PHP
Python

Clojure
Java
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

via applications

yes

user defined functions and integration of map-reduce

yes

Java Stored Procedures

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

yes

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

via Faunus, a graph analytics engine

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

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

User concepts

Access control

Users and groups

Can implement custom security layer via applications

Access rights for users, groups and roles

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

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