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DBMS > Google BigQuery vs. Microsoft Azure Cosmos DB vs. Oracle NoSQL

System Properties Comparison Google BigQuery vs. Microsoft Azure Cosmos DB vs. Oracle NoSQL

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonOracle NoSQL  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesGlobally distributed, horizontally scalable, multi-model database serviceA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes
Primary database modelRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Document store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score45.62
Rank#24  Overall
#16  Relational DBMS
Score40.04
Rank#26  Overall
#3  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score4.41
Rank#81  Overall
#14  Document stores
#13  Key-value stores
#44  Relational DBMS
Websitecloud.google.com/­bigqueryazure.microsoft.com/­services/­cosmos-dbwww.oracle.com/­database/­technologies/­related/­nosql.html
Technical documentationcloud.google.com/­bigquery/­docsdocs.microsoft.com/­azure/­cosmos-dbdocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.html
DeveloperGoogleMicrosoftOracle
Initial release201020142011
Current release21.2, September 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedhostedLinux
Solaris SPARC/x86
Data schemeyesschema-freeSupport Fixed schema and Schema-less deployment with the ability to interoperate between them.
Typing infopredefined data types such as float or dateyesyes infoJSON typesoptional
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 indexesnoyes infoAll properties auto-indexed by defaultyes
SQL infoSupport of SQLyesSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP/JSON APIDocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
RESTful HTTP API
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
C
C#
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptJavaScriptno
TriggersnoJavaScriptno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceElectable source-replica replication per shard. Support distributed global deployment with Multi-region table feature
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*with Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Eventual Consistency
Immediate Consistency infodepending on configuration
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataMulti-item ACID transactions with snapshot isolation within a partitionconfigurable infoACID within a storage node (=shard)
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infooff heap cache
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Access rights can be defined down to the item levelAccess rights for users and roles

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More resources
Google BigQueryMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBOracle NoSQL
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