DBMS > Databend vs. Fujitsu Enterprise Postgres vs. Geode vs. RDF4J

System Properties Comparison Databend vs. Fujitsu Enterprise Postgres vs. Geode vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

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

Primary database model

Relational DBMS

Key-value store

RDF store

Secondary database models

Document store
Spatial DBMS

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

Score	0.27
Rank	#289	Overall
	#131	Relational DBMS

Score	0.24
Rank	#297	Overall
	#134	Relational DBMS

Score	1.42
Rank	#149	Overall
	#25	Key-value stores

Score	0.82
Rank	#208	Overall
	#7	RDF stores

Website

github.com/datafuselabs/databend
www.databend.com

www.postgres.global.fujitsu.com

geode.apache.org

rdf4j.org

Technical documentation

docs.databend.com

www.postgres.global.fujitsu.com/product-manuals

geode.apache.org/docs

rdf4j.org/documentation

Developer

Databend Labs

Fujitsu Limited

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

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

Initial release

2021

2002

2004

Current release

1.0.59, April 2023

Fujitsu Enterprise Postgres 16, May 2024

1.1, February 2017

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Rust

Java

Server operating systems

hosted
Linux
macOS

Linux
Windows

All OS with a Java VM

the JDK (8 or later) is also required

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (OQL)

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

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

Java Client API
Memcached protocol
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

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

.Net
All JVM based languages
C++
Groovy
Java
Scala

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

partitioning by range, list and by hash

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

yes, on a single node

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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

Users with fine-grained authorization concept, user roles

fine grained access rights according to SQL-standard

Access rights per client and object definable

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