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DBMS > Google BigQuery vs. Kdb

System Properties Comparison Google BigQuery vs. Kdb

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonKdb  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesHigh performance Time Series DBMS
Primary database modelRelational DBMSTime Series DBMS
Vector DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score63.63
Rank#19  Overall
#13  Relational DBMS
Score8.27
Rank#52  Overall
#3  Time Series DBMS
#1  Vector DBMS
Websitecloud.google.com/­bigquerykx.com
Technical documentationcloud.google.com/­bigquery/­docscode.kx.com
DeveloperGoogleKx Systems, a division of First Derivatives plc
Initial release20102000 infokdb was released 2000, kdb+ in 2003
Current release3.6, May 2018
License infoCommercial or Open Sourcecommercialcommercial infofree 32-bit version
Cloud-based only infoOnly available as a cloud serviceyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageq
Server operating systemshostedLinux
OS X
Solaris
Windows
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.noyes
Secondary indexesnoyes infotable attribute 'grouped'
SQL infoSupport of SQLyesSQL-like query language (q)
APIs and other access methodsRESTful HTTP/JSON APIHTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Supported programming languages.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 infoStored proceduresuser defined functions infoin JavaScriptuser defined functions
Triggersnoyes infowith views
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infosimilar paradigm used for internal processing
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying datano
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)rights management via user accounts
More information provided by the system vendor
Google BigQueryKdb
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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More resources
Google BigQueryKdb
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