DBMS > Cachelot.io vs. KairosDB vs. RRDtool vs. Vertica

System Properties Comparison Cachelot.io vs. KairosDB vs. RRDtool vs. Vertica

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

In-memory caching system

Distributed Time Series DBMS based on Cassandra or H2

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.

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Key-value store

Time Series DBMS

Relational DBMS

Column oriented

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.00
Rank	#396	Overall
	#64	Key-value stores

Score	0.71
Rank	#230	Overall
	#20	Time Series DBMS

Score	2.14
Rank	#124	Overall
	#10	Time Series DBMS

Score	11.40
Rank	#43	Overall
	#27	Relational DBMS

Website

cachelot.io

github.com/kairosdb/kairosdb

oss.oetiker.ch/rrdtool

www.vertica.com

Technical documentation

kairosdb.github.io

oss.oetiker.ch/rrdtool/doc

vertica.com/documentation

Developer

Tobias Oetiker

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2015

2013

1999

2005

Current release

1.2.2, November 2018

1.8.0, 2022

12.0.3, January 2023

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

Apache 2.0

Open Source

GPL V2 and FLOSS

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

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

C++

Server operating systems

FreeBSD
Linux
OS X

Linux
OS X
Windows

HP-UX
Linux

Linux

Data scheme

schema-free

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

Memcached protocol

Graphite protocol
HTTP REST
Telnet API

in-process shared library
Pipes

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

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

Java
JavaScript

Node.js
PHP
Python

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#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

none

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

simple password-based access control

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more

Competitive advantages

Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more

Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

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

show all

Recent citations in the news

Expo: Real Time A/B Testing and Monitoring with Spark Streaming and Kafka at Walmart Labs
24 May 2019, InfoQ.com

provided by Google News

SQLi vulnerability in Cacti could lead to RCE (CVE-2023-51448)
9 January 2024, Help Net Security

Cacti: Using Graphs to Monitor Networks and Devices
16 March 2011, Packt Hub

A plotting utility for text mode consoles and terminals @tenox77
28 June 2023, Adafruit Blog

How to install Cacti SNMP Monitor on Ubuntu
24 November 2017, TechRepublic

Installation Guide for Collectd and Collectd-Web to Monitor Server Resources in Linux
29 November 2017, Linux.com

provided by Google News

OCI Object Storage Completes Technical Validation of Vertica in Eon Mode
16 October 2023, Oracle

Vertica by OpenText and Anritsu Sign New Deal for Next-Gen Architecture and 5G Network Capabilities
17 May 2023, PR Newswire

Stonebraker Seeks to Invert the Computing Paradigm with DBOS
12 March 2024, Datanami

OpenText expands enterprise portfolio with AI and Micro Focus integrations
25 July 2023, VentureBeat

OpenText integrates Micro Focus tech through Cloud Editions 23.3
26 July 2023, Techzine Europe

provided by Google News

Share this page