DBMS > KairosDB vs. MySQL vs. RocksDB vs. Trafodion vs. Vertica

System Properties Comparison KairosDB vs. MySQL vs. RocksDB vs. Trafodion vs. Vertica

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Distributed Time Series DBMS based on Cassandra or H2

Widely used open source RDBMS

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Transactional SQL-on-Hadoop DBMS

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

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Key-value store

Relational DBMS

Column oriented

Secondary database models

Document store
Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

github.com/kairosdb/kairosdb

Technical documentation

kairosdb.github.io

dev.mysql.com/doc

github.com/facebook/rocksdb/wiki

trafodion.apache.org/documentation.html

vertica.com/documentation

Developer

Oracle

since 2010, originally MySQL AB, then Sun

Facebook, Inc.

Apache Software Foundation, originally developed by HP

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2013

1995

2013

2014

2005

Current release

1.2.2, November 2018

8.4.0, April 2024

9.2.1, May 2024

2.3.0, February 2019

12.0.3, January 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

BSD

Open Source

Apache 2.0

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.

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Implementation language

Java

C and C++

C++

C++, Java

C++

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

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

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.

yes

Secondary indexes

yes

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

SQL

Support of SQL

yes

with proprietary extensions

yes

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

APIs and other access methods

Graphite protocol
HTTP REST
Telnet API

ADO.NET
JDBC
ODBC
Proprietary native API

C++ API
Java API

ADO.NET
JDBC
ODBC

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

character-based, interactive, front-end utility

Supported programming languages

Java
JavaScript

Node.js
PHP
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Go
Java
Perl
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

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

Server-side scripts

Stored procedures

yes

proprietary syntax

Java Stored Procedures

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

Sharding

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

yes

yes, via HBase

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

yes

via user defined functions and HBase

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing models

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