DBMS > atoti vs. RDF4J vs. TimescaleDB

System Properties Comparison atoti vs. RDF4J vs. TimescaleDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Object oriented DBMS

RDF store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.83
Rank	#241	Overall
	#10	Object oriented DBMS

Score	1.06
Rank	#214	Overall
	#9	RDF stores

Score	5.38
Rank	#77	Overall
	#4	Time Series DBMS

Website

atoti.io

rdf4j.org

www.timescale.com

Technical documentation

docs.atoti.io

rdf4j.org/documentation

docs.timescale.com

Developer

ActiveViam

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

Timescale

Initial release

2004

2017

Current release

2.11.0, May 2023

License

Commercial or Open Source

commercial

free versions available

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache 2.0

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

Java

Server operating systems

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

Multidimensional Expressions (MDX)

yes

full PostgreSQL SQL syntax

APIs and other access methods

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

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

Supported programming languages

Java
PHP
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Python

yes

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

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, multi-version concurrency control (MVCC)

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Virtual screening of functional foods and dissecting their roles in ...
22 October 2021, onlinelibrary.wiley.com

provided by Google News

Ontotext's GraphDB 10 Brings Modern Data Architectures to the ...
5 July 2022, PR Newswire

Intara FAQs
16 November 2022, Jane's

SPARQL, le SQL du Web, et Linked Data Fragment : le point sur le ...
1 January 2017, linuxfr.org

provided by Google News

TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

InfluxDB Clustered targets on-premises time-series database deployments
6 September 2023, InfoWorld

Introduction to Databases in Data Science
8 September 2023, KDnuggets

Visualizing IoT Data at Scale With Hopara and TimescaleDB
16 May 2023, Embedded Computing Design

TimescaleDB setzt nun auch auf Vektordatenbanken | heise online
26 September 2023, heise online

provided by Google News

Job opportunities

Ontologist
Johns Hopkins Applied Physics Laboratory (APL), Laurel, MD

Rust Engineers (Multiple Openings) - Remote
Keyrock, Remote

Data & Machine Learning Engineer
Hewlett Packard Enterprise, Spring, TX

Data & Machine Learning Engineer
Hewlett-Packard CDS GmbH, Houston, TX

Financial Markets Data Specialist
Federal Reserve Bank of New York, New York, NY

Infrastructure Engineer
Messari, Remote

jobs by

Share this page