DBMS > EXASOL vs. Google BigQuery vs. Kdb

System Properties Comparison EXASOL vs. Google BigQuery vs. Kdb

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Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Large scale data warehouse service with append-only tables

High performance Time Series DBMS

Primary database model

Relational DBMS

Time Series DBMS
Vector DBMS

Secondary database models

Relational DBMS

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

Score	2.25
Rank	#120	Overall
	#57	Relational DBMS

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	7.70
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Website

www.exasol.com

cloud.google.com/bigquery

kx.com

Technical documentation

www.exasol.com/resources

cloud.google.com/bigquery/docs

code.kx.com

Developer

Exasol

Google

Kx Systems, a division of First Derivatives plc

Initial release

2000

2010

2000

kdb was released 2000, kdb+ in 2003

Current release

3.6, May 2018

License

Commercial or Open Source

commercial

free 32-bit version

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

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'

SQL

Support of SQL

yes

SQL-like query language (q)

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

RESTful HTTP/JSON API

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

Supported programming languages

Java
Lua
Python
R

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

in JavaScript

user defined functions

Triggers

yes

with views

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

Since BigQuery is designed for querying data

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 according to SQL-standard

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

rights management via user accounts

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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.