DBMS > EsgynDB vs. Kdb vs. Microsoft Azure Table Storage vs. SAP HANA vs. UniData,UniVerse

System Properties Comparison EsgynDB vs. Kdb vs. Microsoft Azure Table Storage vs. SAP HANA vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

High performance Time Series DBMS

A Wide Column Store for rapid development using massive semi-structured datasets

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

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Relational DBMS

Time Series DBMS
Vector DBMS

Wide column store

Relational DBMS

Multivalue DBMS

Secondary database models

Relational 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	0.16
Rank	#329	Overall
	#146	Relational DBMS

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

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

www.esgyn.cn

kx.com

azure.microsoft.com/en-us/services/storage/tables

www.sap.com/products/hana.html

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

Technical documentation

code.kx.com

help.sap.com/hana

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Esgyn

Kx Systems, a division of First Derivatives plc

Microsoft

SAP

Rocket Software

Initial release

2015

2000

kdb was released 2000, kdb+ in 2003

2012

2010

1985

Current release

3.6, May 2018

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

free 32-bit version

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java

Server operating systems

Linux

Linux
OS X
Solaris
Windows

hosted

Appliance or cloud-service

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

table attribute 'grouped'

yes

SQL

Support of SQL

yes

SQL-like query language (q)

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

RESTful HTTP API

JDBC
ODBC

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

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

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

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

SQLScript, R

yes

Triggers

yes

with views

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Implicit feature of the cloud service

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

similar paradigm used for internal processing

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

optimistic locking

ACID

configurable

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

fine grained access rights according to SQL-standard

rights management via user accounts

Access rights based on private key authentication or shared access signatures

yes

Access rights according to SQL-standard and operating system based

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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