DBMS > GeoMesa vs. RRDtool vs. Sadas Engine vs. Transwarp ArgoDB

System Properties Comparison GeoMesa vs. RRDtool vs. Sadas Engine vs. Transwarp ArgoDB

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Editorial information provided by DB-Engines

Name

Description

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

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.

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Spatial DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Search engine

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.12
Rank	#348	Overall
	#151	Relational DBMS

Website

www.geomesa.org

oss.oetiker.ch/rrdtool

www.sadasengine.com

www.transwarp.cn/en/product/argodb

Technical documentation

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

oss.oetiker.ch/rrdtool/doc

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

CCRi and others

Tobias Oetiker

SADAS s.r.l.

Transwarp

Initial release

2014

1999

2006

Current release

5.0.0, May 2024

1.8.0, 2022

8.0

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

GPL V2 and FLOSS

commercial

free trial version available

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

Scala

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

C++

Server operating systems

HP-UX
Linux

AIX
Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

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

yes

APIs and other access methods

in-process shared library
Pipes

JDBC
ODBC
Proprietary protocol

Supported programming languages

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

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

managed by 'Learn by Usage'

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights for users, groups and roles according to SQL-standard

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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