DBMS > Databricks vs. Kdb vs. Microsoft Azure AI Search vs. Snowflake

System Properties Comparison Databricks vs. Kdb vs. Microsoft Azure AI Search vs. Snowflake

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

High performance Time Series DBMS

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

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

Primary database model

Document store
Relational DBMS

Time Series DBMS
Vector DBMS

Search engine

Relational DBMS

Secondary database models

Relational DBMS

Vector DBMS

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

Score	81.08
Rank	#15	Overall
	#2	Document stores
	#10	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	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.databricks.com

kx.com

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

www.snowflake.com

Technical documentation

docs.databricks.com

code.kx.com

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

docs.snowflake.net/manuals/index.html

Developer

Databricks

Kx Systems, a division of First Derivatives plc

Microsoft

Snowflake Computing Inc.

Initial release

2013

2000

kdb was released 2000, kdb+ in 2003

2015

2014

Current release

3.6, May 2018

License

Commercial or Open Source

commercial

free 32-bit version

commercial

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

Server operating systems

hosted

Linux
OS X
Solaris
Windows

hosted

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

yes

support of semi-structured data formats (JSON, XML, Avro)

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

with Databricks SQL

SQL-like query language (q)

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

Python
R
Scala

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

C#
Java
JavaScript
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

Triggers

yes

with views

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Implicit feature of the cloud service

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

Implicit feature of the cloud service

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

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

rights management via user accounts

yes

using Azure authentication

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

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
» more

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.