DBMS > Cachelot.io vs. GeoMesa vs. RRDtool vs. Splunk

System Properties Comparison Cachelot.io vs. GeoMesa vs. RRDtool vs. Splunk

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Editorial information provided by DB-Engines

Name

Description

In-memory caching system

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.

Analytics Platform for Big Data

Primary database model

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

Score	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

cachelot.io

www.geomesa.org

oss.oetiker.ch/rrdtool

www.splunk.com

Technical documentation

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

oss.oetiker.ch/rrdtool/doc

docs.splunk.com/Documentation/Splunk

Developer

CCRi and others

Tobias Oetiker

Splunk Inc.

Initial release

2015

2014

1999

2003

Current release

5.0.0, May 2024

1.8.0, 2022

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

Apache License 2.0

Open Source

GPL V2 and FLOSS

commercial

Limited free edition and free developer edition available

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

C++

Scala

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

Server operating systems

FreeBSD
Linux
OS X

HP-UX
Linux

Linux
OS X
Solaris
Windows

Data scheme

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.

Exporting into and restoring from XML files possible

yes

Secondary indexes

yes

SQL

Support of SQL

Splunk Search Processing Language for search commands

APIs and other access methods

Memcached protocol

in-process shared library
Pipes

HTTP REST

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

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

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

depending on storage layer

none

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

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

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights for users and roles

More information provided by the system vendor

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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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Enterprise Search Engines almost double their popularity in the last 12 months
2 July 2014, Paul Andlinger

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