DBMS > GeoMesa vs. Graphite vs. Riak KV vs. Yaacomo

System Properties Comparison GeoMesa vs. Graphite vs. Riak KV vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

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

Distributed, fault tolerant key-value store

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Spatial DBMS

Time Series DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

www.geomesa.org

github.com/graphite-project/graphite-web

yaacomo.com

Technical documentation

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

graphite.readthedocs.io

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

Developer

CCRi and others

Chris Davis

OpenSource, formerly Basho Technologies

Q2WEB GmbH

Initial release

2014

2006

2009

Current release

5.0.0, May 2024

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

Apache version 2, commercial enterprise edition

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

Python

Erlang

Server operating systems

Linux
Unix

Linux
OS X

Android
Linux
Windows

Data scheme

yes

schema-free

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.

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP API
Sockets

HTTP API
Native Erlang Interface

JDBC
ODBC

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

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

none

Sharding

no "single point of failure"

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

none

selectable replication factor

Source-replica replication

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

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

yes

Transaction concepts

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

ACID

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

yes

User concepts

Access control

yes

depending on the DBMS used for storage

yes, using Riak Security

fine grained access rights 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

show all

Recent citations in the news

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

Grafana Labs Announces Mimir Time Series Database
1 April 2022, Datanami

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

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

The value of time series data and TSDBs
10 June 2021, InfoWorld

provided by Google News

Basho Revamps Riak Open-Source Database
22 September 2023, InformationWeek

A Critique of Resizable Hash Tables: Riak Core & Random Slicing
26 August 2018, InfoQ.com

Riak NoSQL snapped up by Bet365
12 September 2017, ComputerWeekly.com

Basho to Bolster Riak with DB Plug-Ins
5 May 2014, Datanami

Basho Advances NoSQL Riak Enterprise 2.0 With Search, Advanced Data Types
15 September 2014, Data Center Knowledge

provided by Google News

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