DBMS > Apache IoTDB vs. H2GIS vs. RDF4J vs. SQream DB

System Properties Comparison Apache IoTDB vs. H2GIS vs. RDF4J vs. SQream DB

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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

Spatial extension of H2

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

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Secondary database models

Relational DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

Technical documentation

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

www.h2gis.org/docs/home

rdf4j.org/documentation

docs.sqream.com

Developer

Apache Software Foundation

CNRS

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

SQream Technologies

Initial release

2018

2013

2004

2017

Current release

1.1.0, April 2023

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

LGPL 3.0

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

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++, CUDA, Haskell, Java, Scala

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X
Unix
Windows

Linux

Data scheme

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL 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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

.Net
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Java

Java
PHP
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

based on H2

yes

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

horizontal and vertical partitioning

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

yes

based on H2

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

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

yes

based on H2

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