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DBMS > Apache Impala vs. Google BigQuery

System Properties Comparison Apache Impala vs. Google BigQuery

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle BigQuery  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopLarge scale data warehouse service with append-only tables
Primary database modelRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.39
Rank#41  Overall
#25  Relational DBMS
Score52.29
Rank#19  Overall
#13  Relational DBMS
Websiteimpala.apache.orgcloud.google.com/­bigquery
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigquery/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogle
Initial release20132010
Current release4.1.0, June 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemsLinuxhosted
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 indexesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions infoin JavaScript
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoSince BigQuery is designed for querying data
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 rights for users, groups and roles infobased on Apache Sentry and KerberosAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)

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More resources
Apache ImpalaGoogle BigQuery
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