DBMS > AgensGraph vs. Cloudflare Workers KV vs. RDF4J vs. Transbase

System Properties Comparison AgensGraph vs. Cloudflare Workers KV vs. RDF4J vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

A global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.

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

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Graph DBMS
Relational DBMS

Key-value store

RDF store

Relational DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	0.32
Rank	#283	Overall
	#40	Key-value stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

bitnine.net/agensgraph

www.cloudflare.com/developer-platform/workers-kv

rdf4j.org

www.transaction.de/en/products/transbase.html

Technical documentation

bitnine.net/documentation

developers.cloudflare.com/kv/api

rdf4j.org/documentation

www.transaction.de/en/products/transbase/features.html

Developer

Bitnine Global Inc.

Cloudflare

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

Transaction Software GmbH

Initial release

2016

2018

2004

1987

Current release

2.1, December 2018

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

free development license

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

C and C++

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X
Unix
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

depending on used data model

schema-free

yes

RDF Schemas

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Cypher Query Language
JDBC

HTTP REST
Proprietary protocol

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
Java
JavaScript
Python

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

Java
PHP
Python

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

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