DBMS > GeoMesa vs. Graphite vs. Riak TS

System Properties Comparison GeoMesa vs. Graphite vs. Riak TS

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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.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Spatial DBMS

Time Series DBMS

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

www.geomesa.org

github.com/graphite-project/graphite-web

Technical documentation

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

graphite.readthedocs.io

www.tiot.jp/riak-docs/riak/ts/latest

Developer

CCRi and others

Chris Davis

Open Source, formerly Basho Technologies

Initial release

2014

2006

2015

Current release

4.0.5, February 2024

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

Python

Erlang

Server operating systems

Linux
Unix

Linux
OS X

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

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

restricted

SQL

Support of SQL

yes, limited

APIs and other access methods

HTTP API
Sockets

HTTP API
Native Erlang Interface

Supported programming languages

JavaScript (Node.js)
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

none

selectable replication factor

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

Eventual Consistency

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

locking

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

User concepts

Access control

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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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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Recent citations in the news

Try out the Graphite monitoring tool for time-series data
29 October 2019, TechTarget

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1 April 2022, Datanami

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12 June 2023, InfoWorld

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
10 December 2018, Uber

Getting Started with Monitoring using Graphite
23 January 2015, InfoQ.com

provided by Google News

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26 May 2017, Open Source For You

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