DBMS > Apache IoTDB vs. Apache Jena - TDB vs. Brytlyt vs. Lovefield vs. RDF4J

System Properties Comparison Apache IoTDB vs. Apache Jena - TDB vs. Brytlyt vs. Lovefield vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

A RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena framework

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Embeddable relational database for web apps written in pure JavaScript

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

Primary database model

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	3.62
Rank	#83	Overall
	#3	RDF stores

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

iotdb.apache.org

jena.apache.org/documentation/tdb/index.html

brytlyt.io

google.github.io/lovefield

rdf4j.org

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

jena.apache.org/documentation/tdb/index.html

docs.brytlyt.io

github.com/google/lovefield/blob/master/docs/spec_index.md

rdf4j.org/documentation

Developer

Apache Software Foundation

originally developed by HP Labs

Brytlyt

Google

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

Initial release

2018

2000

2016

2014

2004

Current release

1.1.0, April 2023

4.9.0, July 2023

5.0, August 2023

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache License, Version 2.0

commercial

Open Source

Apache 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

Java

C, C++ and CUDA

JavaScript

Java

Server operating systems

All OS with a Java VM (>= 1.8)

All OS with a Java VM

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Unix
Windows

Data scheme

yes

RDF Schemas

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
Native API

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Java

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

JavaScript

Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions

in PL/pgSQL

yes

Triggers

yes

via event handler

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

TDB Transactions

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

using MemoryDB

User concepts

Access control

yes

Access control via Jena Security

fine grained access rights according to SQL-standard

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