DBMS > Apache Impala vs. Kdb vs. Microsoft Azure AI Search vs. SAP HANA

System Properties Comparison Apache Impala vs. Kdb vs. Microsoft Azure AI Search vs. SAP HANA

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

High performance Time Series DBMS

Search-as-a-service for web and mobile app development

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

Primary database model

Relational DBMS

Time Series DBMS
Vector DBMS

Search engine

Relational DBMS

Secondary database models

Document store

Relational DBMS

Vector 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	12.45
Rank	#40	Overall
	#24	Relational DBMS

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

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

impala.apache.org

kx.com

azure.microsoft.com/en-us/services/search

www.sap.com/products/hana.html

Technical documentation

impala.apache.org/impala-docs.html

code.kx.com

learn.microsoft.com/en-us/azure/search

help.sap.com/hana

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Kx Systems, a division of First Derivatives plc

Microsoft

SAP

Initial release

2013

2000

kdb was released 2000, kdb+ in 2003

2015

2010

Current release

4.1.0, June 2022

3.6, May 2018

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2

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++

Server operating systems

Linux

Linux
OS X
Solaris
Windows

hosted

Appliance or cloud-service

Data scheme

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

table attribute 'grouped'

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language (q)

yes

APIs and other access methods

JDBC
ODBC

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

RESTful HTTP API

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

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

C#
Java
JavaScript
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

SQLScript, R

Triggers

yes

with views

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Implicit feature of the cloud service

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

rights management via user accounts

yes

using Azure authentication

yes

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.