DBMS > Fujitsu Enterprise Postgres vs. jBASE vs. MonetDB vs. Neo4j vs. Snowflake

System Properties Comparison Fujitsu Enterprise Postgres vs. jBASE vs. MonetDB vs. Neo4j vs. Snowflake

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.

A robust multi-value DBMS comprising development tools and middleware

A relational database management system that stores data in columns

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.37
Rank	#278	Overall
	#128	Relational DBMS

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	44.89
Rank	#21	Overall
	#1	Graph DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.postgresql.fastware.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

www.monetdb.org

neo4j.com

www.snowflake.com

Technical documentation

www.postgresql.fastware.com/product-manuals

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

www.monetdb.org/Documentation

neo4j.com/docs

docs.snowflake.net/manuals/index.html

Developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Rocket Software (formerly Zumasys)

MonetDB BV

Neo4j, Inc.

Snowflake Computing Inc.

Initial release

1991

2004

2007

2014

Current release

Fujitsu Enterprise Postgres 14, January 2022

5.7

Dec2023 (11.49), December 2023

5.20, May 2024

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

Open Source

GPL version3, commercial licenses 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.

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

Java, Scala

Server operating systems

Linux
Windows

AIX
Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

hosted

Data scheme

yes

schema-free

yes

schema-free and schema-optional

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

optional

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

pluggable indexing subsystem, by default Apache Lucene

SQL

Support of SQL

yes

Embedded SQL for jBASE in BASIC

yes

SQL 2003 with some extensions

yes

APIs and other access methods

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

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

CLI Client
JDBC
ODBC

Supported programming languages

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

.Net
Basic
Jabbascript
Java

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

yes, in SQL, C, R

yes

User defined Procedures and Functions

user defined functions

Triggers

yes

via event handler

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

Sharding

Sharding via remote tables

yes using Neo4j Fabric

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

Source-replica replication available in experimental status

Causal Clustering using Raft protocol

available in in Enterprise Version only

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

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, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

Users with fine-grained authorization concept, user roles and pluggable authentication

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