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DBMS > GBase vs. Google BigQuery vs. Spark SQL

System Properties Comparison GBase vs. Google BigQuery vs. Spark SQL

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Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn analytical database for business intelligence with large customers in China.Large scale data warehouse service with append-only tablesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.05
Rank#193  Overall
#90  Relational DBMS
Score62.67
Rank#19  Overall
#13  Relational DBMS
Score19.56
Rank#34  Overall
#21  Relational DBMS
Websitewww.gbase.cncloud.google.com/­bigqueryspark.apache.org/­sql
Technical documentationcloud.google.com/­bigquery/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleApache Software Foundation
Initial release20102014
Current releaseGBase 8a3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScala
Server operating systemshostedLinux
OS X
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.nono
Secondary indexesnono
SQL infoSupport of SQLyesSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP/JSON APIJDBC
ODBC
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynono
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.nono
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)no

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More resources
GBaseGoogle BigQuerySpark SQL
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