DBMS > Kdb vs. Postgres-XL vs. SiteWhere vs. Snowflake vs. Trafodion

System Properties Comparison Kdb vs. Postgres-XL vs. SiteWhere vs. Snowflake vs. Trafodion

Editorial information provided by DB-Engines

Name

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

Description

High performance Time Series DBMS

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

M2M integration platform for persisting/querying time series data

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

Transactional SQL-on-Hadoop DBMS

Primary database model

Time Series DBMS
Vector DBMS

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	7.71
Rank	#49	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

kx.com

www.postgres-xl.org

github.com/sitewhere/sitewhere

www.snowflake.com

trafodion.apache.org

Technical documentation

code.kx.com

www.postgres-xl.org/documentation

sitewhere1.sitewhere.io/index.html

docs.snowflake.net/manuals/index.html

trafodion.apache.org/documentation.html

Developer

Kx Systems, a division of First Derivatives plc

SiteWhere

Snowflake Computing Inc.

Apache Software Foundation, originally developed by HP

Initial release

2000

kdb was released 2000, kdb+ in 2003

2014

since 2012, originally named StormDB

2010

2014

Current release

3.6, May 2018

10 R1, October 2018

2.3.0, February 2019

License

Commercial or Open Source

commercial

free 32-bit version

Open Source

Mozilla public license

Open Source

Common Public Attribution License Version 1.0

commercial

Open Source

Apache 2.0

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++, Java

Server operating systems

Linux
OS X
Solaris
Windows

Linux
macOS

Linux
OS X
Windows

hosted

Linux

Data scheme

yes

predefined scheme

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

XML type, but no XML query functionality

yes

Secondary indexes

yes

table attribute 'grouped'

yes

SQL

Support of SQL

SQL-like query language (q)

yes

distributed, parallel query execution

yes

APIs and other access methods

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP REST

CLI Client
JDBC
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

Triggers

yes

with views

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

based on HBase

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on HBase

yes

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

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

User concepts

Access control

rights management via user accounts

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
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Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

upon request
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