DBMS > KairosDB vs. Manticore Search vs. MySQL vs. SAP HANA vs. SiteWhere

System Properties Comparison KairosDB vs. Manticore Search vs. MySQL vs. SAP HANA vs. SiteWhere

Editorial information provided by DB-Engines

Name

Description

Distributed Time Series DBMS based on Cassandra or H2

Multi-storage database for search, including full-text search.

Widely used open source RDBMS

In-memory, column based data store. Available as appliance or cloud service

M2M integration platform for persisting/querying time series data

Primary database model

Time Series DBMS

Search engine

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Time Series DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

github.com/kairosdb/kairosdb

manticoresearch.com

www.mysql.com

www.sap.com/products/hana.html

github.com/sitewhere/sitewhere

Technical documentation

kairosdb.github.io

manual.manticoresearch.com

dev.mysql.com/doc

help.sap.com/hana

sitewhere1.sitewhere.io/index.html

Developer

Manticore Software

Oracle

since 2010, originally MySQL AB, then Sun

SAP

SiteWhere

Initial release

2013

2017

1995

2010

Current release

1.2.2, November 2018

6.0, February 2023

8.4.0, April 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

Common Public Attribution License Version 1.0

Cloud-based only

Only available as a cloud service

also available as a cloud based service

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Database as a Service

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Implementation language

Java

C++

C and C++

Java

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
macOS
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Appliance or cloud-service

Linux
OS X
Windows

Data scheme

schema-free

Fixed schema

yes

predefined scheme

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

yes

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

yes

APIs and other access methods

Graphite protocol
HTTP REST
Telnet API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

HTTP REST

Supported programming languages

Java
JavaScript

Node.js
PHP
Python

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Partitioning is done manually, search queries against distributed index is supported

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Synchronous replication based on Galera library

Multi-source replication
Source-replica replication

yes

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

not for MyISAM storage engine

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

The original contents of fields are not stored in the Manticore index.

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

yes

Users with fine-grained authorization concept

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