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DBMS > Google BigQuery vs. Hive vs. Spark SQL vs. SQLite vs. Transbase

System Properties Comparison Google BigQuery vs. Hive vs. Spark SQL vs. SQLite vs. Transbase

Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonHive  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQLite  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesdata warehouse software for querying and managing large distributed datasets, built on HadoopSpark SQL is a component on top of 'Spark Core' for structured data processingWidely used embeddable, in-process RDBMSA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score58.10
Rank#19  Overall
#13  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score111.41
Rank#10  Overall
#7  Relational DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitecloud.google.com/­bigqueryhive.apache.orgspark.apache.org/­sqlwww.sqlite.orgwww.transaction.de/­en/­products/­transbase.html
Technical documentationcloud.google.com/­bigquery/­docscwiki.apache.org/­confluence/­display/­Hive/­Homespark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.sqlite.org/­docs.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperGoogleApache Software Foundation infoinitially developed by FacebookApache Software FoundationDwayne Richard HippTransaction Software GmbH
Initial release20102012201420001987
Current release3.1.3, April 20223.5.0 ( 2.13), September 20233.46.0  (23 May 2024), May 2024Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoPublic Domaincommercial infofree development license
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScalaCC and C++
Server operating systemshostedAll OS with a Java VMLinux
OS X
Windows
server-lessFreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyesyesyes infodynamic column typesyes
Typing infopredefined data types such as float or dateyesyesyesyes infonot rigid because of 'dynamic typing' concept.yes
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.nononono
Secondary indexesnoyesnoyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsSQL-like DML and DDL statementsyes infoSQL-92 is not fully supportedyes
APIs and other access methodsRESTful HTTP/JSON APIJDBC
ODBC
Thrift
JDBC
ODBC
ADO.NET infoinofficial driver
JDBC infoinofficial driver
ODBC infoinofficial driver
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C++
Java
PHP
Python
Java
Python
R
Scala
Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptyes infouser defined functions and integration of map-reducenonoyes
Triggersnononoyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornonenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying datanonoACIDyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infovia file-system locksyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Access rights for users, groups and rolesnonofine grained access rights according to SQL-standard

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More resources
Google BigQueryHiveSpark SQLSQLiteTransbase
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