DBMS > GreptimeDB vs. RDF4J vs. TerminusDB vs. Virtuoso

System Properties Comparison GreptimeDB vs. RDF4J vs. TerminusDB vs. Virtuoso

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Editorial information provided by DB-Engines

Name

Description

An open source Time Series DBMS built for increased scalability, high performance and efficiency

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Virtuoso is a multi-model hybrid-RDBMS that supports management of data represented as relational tables and/or property graphs

Primary database model

Time Series DBMS

RDF store

Graph DBMS

Document store
Graph DBMS
Native XML DBMS
Relational DBMS
RDF store
Search engine

Secondary database models

Document store
RDF store

Spatial DBMS

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

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Score	4.27
Rank	#73	Overall
	#13	Document stores
	#4	Graph DBMS
	#2	Native XML DBMS
	#39	Relational DBMS
	#2	RDF stores
	#9	Search engines

Website

greptime.com

rdf4j.org

terminusdb.com

virtuoso.openlinksw.com

Technical documentation

docs.greptime.com

rdf4j.org/documentation

terminusdb.github.io/terminusdb/#

docs.openlinksw.com/virtuoso

Developer

Greptime Inc.

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

DataChemist Ltd.

OpenLink Software

Initial release

2022

2004

2018

1998

Current release

11.0.0, January 2023

7.2.11, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GPL V3

Open Source

GPLv2, extended commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Rust

Java

Prolog, Rust

Server operating systems

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X
Unix
Windows

Linux

AIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free, schema definition possible

yes

RDF Schemas

yes

SQL - Standard relational schema
RDF - Quad (S, P, O, G) or Triple (S, P, O)
XML - DTD, XML Schema
DAV - freeform filesystem objects, plus User Defined Types a/k/a Dynamic Extension Type

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 query language (WOQL)

yes

SQL-92, SQL-200x, SQL-3, SQLX

APIs and other access methods

gRPC
HTTP API
JDBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

ADO.NET
GeoSPARQL
HTTP API
JDBC
Jena RDF API
ODBC
OLE DB
RDF4J API
RESTful HTTP API
Sesame REST HTTP Protocol
SOAP webservices
SPARQL 1.1
WebDAV
XPath
XQuery
XSLT

Supported programming languages

C++
Erlang
Go
Java
JavaScript

Java
PHP
Python

JavaScript
Python

.Net
C
C#
C++
Java
JavaScript
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

Python

yes

Virtuoso PL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Graph Partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Journaling Streams

Chain, star, and bi-directional replication
Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

ACID

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 journaling

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

Simple rights management via user accounts

Role-based access control

Fine-grained Attribute-Based Access Control (ABAC) in addition to typical coarse-grained Role-Based Access Control (RBAC) according to SQL-standard. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Virtuoso is a modern multi-model RDBMS for managing data represented as tabular relations...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Performance & Scale — as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Used for — Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Broad use across enterprises and governments including — European Union (EU) US Government...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Largest installed-base of Multi-Model RDBMS for AI-friendly Knowledge Graphs Platform...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

Available in both Commercial Enterprise and Open Source (GPL v2) Editions Feature...
» more

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