DBMS > KairosDB vs. Kinetica vs. MarkLogic vs. Snowflake vs. Transwarp KunDB

System Properties Comparison KairosDB vs. Kinetica vs. MarkLogic vs. Snowflake vs. Transwarp KunDB

Editorial information provided by DB-Engines

Name

Description

Distributed Time Series DBMS based on Cassandra or H2

Fully vectorized database across both GPUs and CPUs

Operational and transactional Enterprise NoSQL database

Cloud-based data warehousing service for structured and semi-structured data

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Time Series DBMS

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Secondary database models

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	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	5.18
Rank	#63	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#7	Search engines

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.14
Rank	#341	Overall
	#149	Relational DBMS

Website

github.com/kairosdb/kairosdb

www.kinetica.com

www.progress.com/marklogic

www.snowflake.com

www.transwarp.cn/en/product/kundb

Technical documentation

kairosdb.github.io

docs.kinetica.com

www.progress.com/marklogic/documentation

docs.snowflake.net/manuals/index.html

Developer

Kinetica

MarkLogic Corp.

Snowflake Computing Inc.

Transwarp

Initial release

2013

2012

2001

2014

Current release

1.2.2, November 2018

7.1, August 2021

11.0, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

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

Java

C, C++

C++

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X
Windows

hosted

Data scheme

schema-free

yes

schema-free

Schema can be enforced

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL92

yes

APIs and other access methods

Graphite protocol
HTTP REST
Telnet API

JDBC
ODBC
RESTful HTTP API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

CLI Client
JDBC
ODBC

Supported programming languages

Java
JavaScript

Node.js
PHP
Python

C++
Java
JavaScript (Node.js)
Python

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

via XQuery or JavaScript

user defined functions

yes

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

yes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

can act as a resource manager in an XA/JTA transaction

ACID

Concurrency

Support for concurrent manipulation of data

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

GPU vRAM or System RAM

yes, with Range Indexes

User concepts

Access control

simple password-based access control

Access rights for users and roles on table level

Role-based access control at the document and subdocument levels

Users with fine-grained authorization concept, user roles and pluggable authentication

yes

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