DBMS > Kdb vs. Microsoft Azure SQL Database vs. NSDb vs. OrigoDB vs. SiteWhere

System Properties Comparison Kdb vs. Microsoft Azure SQL Database vs. NSDb vs. OrigoDB vs. SiteWhere

Editorial information provided by DB-Engines

Name

Description

High performance Time Series DBMS

Database as a Service offering with high compatibility to Microsoft SQL Server

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A fully ACID in-memory object graph database

M2M integration platform for persisting/querying time series data

Primary database model

Time Series DBMS
Vector DBMS

Relational DBMS

Time Series DBMS

Document store
Object oriented DBMS

Time Series DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

kx.com

azure.microsoft.com/en-us/products/azure-sql/database

nsdb.io

origodb.com

github.com/sitewhere/sitewhere

Technical documentation

code.kx.com

docs.microsoft.com/en-us/azure/azure-sql

nsdb.io/Architecture

origodb.com/docs

sitewhere1.sitewhere.io/index.html

Developer

Kx Systems, a division of First Derivatives plc

Microsoft

Robert Friberg et al

SiteWhere

Initial release

2000

kdb was released 2000, kdb+ in 2003

2010

2017

2009

under the name LiveDB

2010

Current release

3.6, May 2018

V12

License

Commercial or Open Source

commercial

free 32-bit version

commercial

Open Source

Apache Version 2.0

Open Source

Common Public Attribution License Version 1.0

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

C++

Java, Scala

Java

Server operating systems

Linux
OS X
Solaris
Windows

hosted

Linux
macOS

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

predefined scheme

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

table attribute 'grouped'

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language (q)

yes

SQL-like query language

APIs and other access methods

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

.NET Client API
HTTP API
LINQ

HTTP REST

Supported programming languages

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

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

Java
Scala

.Net

Server-side scripts

Stored procedures

user defined functions

Transact SQL

yes

Triggers

yes

with views

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, with always 3 replicas available

Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

Write ahead log

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

Role based authorization

Users with fine-grained authorization concept

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
» more

Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more

Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
» more

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...
» more

Licensing and pricing models

upon request
» 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

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