DBMS > GeoMesa vs. RethinkDB vs. RRDtool vs. SiteWhere vs. SwayDB

System Properties Comparison GeoMesa vs. RethinkDB vs. RRDtool vs. SiteWhere vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

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

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

M2M integration platform for persisting/querying time series data

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

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

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

Website

www.geomesa.org

rethinkdb.com

oss.oetiker.ch/rrdtool

github.com/sitewhere/sitewhere

swaydb.simer.au

Technical documentation

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

rethinkdb.com/docs

oss.oetiker.ch/rrdtool/doc

sitewhere1.sitewhere.io/index.html

Developer

CCRi and others

The Linux Foundation

since July 2017

Tobias Oetiker

SiteWhere

Simer Plaha

Initial release

2014

2009

1999

2010

2018

Current release

5.0.0, May 2024

2.4.1, August 2020

1.8.0, 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache Version 2

Open Source

GPL V2 and FLOSS

Open Source

Common Public Attribution License Version 1.0

Open Source

GNU Affero GPL V3.0

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

Scala

C++

Implementations in Java (e.g. RRD4J) and C# available

Java

Scala

Server operating systems

Linux
OS X
Windows

HP-UX
Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

predefined scheme

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

Numeric data only

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.

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

APIs and other access methods

in-process shared library
Pipes

HTTP REST

Supported programming languages

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Triggers

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

range based

none

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Source-replica replication

none

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-document operations

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

by using the rrdcached daemon

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.

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

yes

users and table-level permissions

Users with fine-grained authorization concept

More information provided by the system vendor

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Related products and services

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More resources

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