DBMS > Amazon DocumentDB vs. Cachelot.io vs. RRDtool vs. Splunk

System Properties Comparison Amazon DocumentDB vs. Cachelot.io vs. RRDtool vs. Splunk

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Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

In-memory caching system

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	1.91
Rank	#131	Overall
	#24	Document stores

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

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

aws.amazon.com/documentdb

cachelot.io

oss.oetiker.ch/rrdtool

www.splunk.com

Technical documentation

aws.amazon.com/documentdb/resources

oss.oetiker.ch/rrdtool/doc

docs.splunk.com/Documentation/Splunk

Developer

Tobias Oetiker

Splunk Inc.

Initial release

2019

2015

1999

2003

Current release

1.8.0, 2022

License

Commercial or Open Source

commercial

Open Source

Simplified BSD License

Open Source

GPL V2 and FLOSS

commercial

Limited free edition and free developer edition available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

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

Server operating systems

hosted

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

proprietary protocol using JSON (MongoDB compatible)

Memcached protocol

in-process shared library
Pipes

HTTP REST

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

.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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Atomic single-document operations

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.

yes

User concepts

Access control

Access rights for users and roles

More information provided by the system vendor

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More resources

DB-Engines blog posts

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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Recent citations in the news

A hybrid approach for homogeneous migration to an Amazon DocumentDB elastic cluster | Amazon Web Services
4 June 2024, AWS Blog

AWS announces Amazon DocumentDB zero-ETL integration with Amazon OpenSearch Service
16 May 2024, AWS Blog

Use LangChain and vector search on Amazon DocumentDB to build a generative AI chatbot | Amazon Web Services
20 May 2024, AWS Blog

Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services
29 November 2023, AWS Blog

AWS announces vector search for Amazon DocumentDB
29 November 2023, AWS Blog

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