DBMS > Apache IoTDB vs. Apache Jena - TDB vs. GeoMesa vs. SwayDB

System Properties Comparison Apache IoTDB vs. Apache Jena - TDB vs. GeoMesa vs. SwayDB

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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

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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	3.75
Rank	#84	Overall
	#3	RDF stores

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

iotdb.apache.org

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

www.geomesa.org

swaydb.simer.au

Technical documentation

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

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

www.geomesa.org/documentation/stable/user/index.html

Developer

Apache Software Foundation

originally developed by HP Labs

CCRi and others

Simer Plaha

Initial release

2018

2000

2014

2018

Current release

1.1.0, April 2023

4.9.0, July 2023

4.0.5, February 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache License, Version 2.0

Open Source

Apache License 2.0

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

Scala

Server operating systems

All OS with a Java VM (>= 1.8)

All OS with a Java VM

Data scheme

yes

RDF Schemas

yes

schema-free

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

SQL-like query language

APIs and other access methods

JDBC
Native API

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Java

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

via event handler

Partitioning methods

Methods for storing different data on different nodes

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

none

depending on storage layer

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

depending on storage layer

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

TDB Transactions

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

depending on storage layer

yes

User concepts

Access control

yes

Access control via Jena Security

yes

depending on the DBMS used for storage

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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