DBMS > EXASOL vs. GreptimeDB vs. RDF4J

System Properties Comparison EXASOL vs. GreptimeDB vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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.

Primary database model

Relational DBMS

Time Series DBMS

RDF store

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

www.exasol.com

greptime.com

rdf4j.org

Technical documentation

www.exasol.com/resources

docs.greptime.com

rdf4j.org/documentation

Developer

Exasol

Greptime Inc.

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

Initial release

2000

2022

2004

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free, schema definition possible

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

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

gRPC
HTTP API
JDBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Java
Lua
Python
R

C++
Erlang
Go
Java
JavaScript

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

Concurrency

Support for concurrent manipulation of data

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

Access rights for users, groups and roles according to SQL-standard

Simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

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

Competitive advantages

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

Typical application scenarios

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

Key customers

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

Market metrics

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

Licensing and pricing models

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

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