DBMS > Apache IoTDB vs. GeoMesa vs. KairosDB vs. SpatiaLite

System Properties Comparison Apache IoTDB vs. GeoMesa vs. KairosDB vs. SpatiaLite

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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

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

Distributed Time Series DBMS based on Cassandra or H2

Spatial extension of SQLite

Primary database model

Secondary database models

Relational DBMS

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Website

iotdb.apache.org

www.geomesa.org

github.com/kairosdb/kairosdb

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

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

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

kairosdb.github.io

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Apache Software Foundation

CCRi and others

Alessandro Furieri

Initial release

2018

2014

2013

2008

Current release

1.1.0, April 2023

5.0.0, May 2024

1.2.2, November 2018

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Scala

Java

C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

server-less

Data scheme

yes

schema-free

yes

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

yes

APIs and other access methods

JDBC
Native API

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

depending on storage layer

Sharding

based on Cassandra

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

depending on storage layer

selectable replication factor

based on Cassandra

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

depending on the DBMS used for storage

simple password-based access control

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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Spatial database management systems
6 April 2021, Matthias Gelbmann

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