DBMS > Fujitsu Enterprise Postgres vs. Hive vs. JanusGraph vs. Microsoft SQL Server vs. RDF4J

System Properties Comparison Fujitsu Enterprise Postgres vs. Hive vs. JanusGraph vs. Microsoft SQL Server vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

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

Microsofts flagship relational DBMS

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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Trend Chart

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

www.postgresql.fastware.com

hive.apache.org

janusgraph.org

www.microsoft.com/en-us/sql-server

rdf4j.org

Technical documentation

www.postgresql.fastware.com/product-manuals

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

docs.janusgraph.org

learn.microsoft.com/en-US/sql/sql-server

rdf4j.org/documentation

Developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Apache Software Foundation

initially developed by Facebook

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2012

2017

1989

2004

Current release

Fujitsu Enterprise Postgres 14, January 2022

3.1.3, April 2022

0.6.3, February 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Java

Server operating systems

Linux
Windows

All OS with a Java VM

Linux
OS X
Unix
Windows

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

RDF Schemas

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

SQL-like DML and DDL statements

yes

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC
Thrift

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++
Java
PHP
Python

Clojure
Java
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions and integration of map-reduce

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

Sharding

yes

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

tables can be distributed across several files (horizontal partitioning); sharding through federation

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

yes

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

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

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

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

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
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Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
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Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
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Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
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Licensing and pricing models

Core based licensing
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