DBMS > Heroic vs. Kdb vs. Kinetica vs. Microsoft Azure SQL Database vs. OpenQM

System Properties Comparison Heroic vs. Kdb vs. Kinetica vs. Microsoft Azure SQL Database vs. OpenQM

Editorial information provided by DB-Engines

Name

Description

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

High performance Time Series DBMS

Fully vectorized database across both GPUs and CPUs

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

QpenQM is a high-performance, self-tuning, multi-value DBMS

Primary database model

Time Series DBMS

Time Series DBMS
Vector DBMS

Relational DBMS

Multivalue DBMS

Secondary database models

Relational DBMS

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

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

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Website

github.com/spotify/heroic

kx.com

www.kinetica.com

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

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

Technical documentation

spotify.github.io/heroic

code.kx.com

docs.kinetica.com

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

Developer

Spotify

Kx Systems, a division of First Derivatives plc

Kinetica

Microsoft

Rocket Software, originally Martin Phillips

Initial release

2014

2000

kdb was released 2000, kdb+ in 2003

2012

2010

1993

Current release

3.6, May 2018

7.1, August 2021

V12

3.4-12

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free 32-bit version

commercial

Open Source

GPLv2, extended commercial license available

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
Solaris
Windows

Linux

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

schema-free

yes

with some exceptions

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

via Elasticsearch

yes

table attribute 'grouped'

yes

SQL

Support of SQL

SQL-like query language (q)

SQL-like DML and DDL statements

yes

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

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

C++
Java
JavaScript (Node.js)
Python

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

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

Transact SQL

yes

Triggers

yes

with views

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes, with always 3 replicas available

yes

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

Eventual Consistency
Immediate Consistency

Immediate Consistency

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

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

User concepts

Access control

rights management via user accounts

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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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