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DBMS > Google BigQuery vs. Microsoft Azure Cosmos DB vs. PlanetScale

System Properties Comparison Google BigQuery vs. Microsoft Azure Cosmos DB vs. PlanetScale

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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 comparisonPlanetScale  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesGlobally distributed, horizontally scalable, multi-model database serviceScalable, distributed, serverless MySQL database platform built on top of Vitess
Primary database modelRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score58.10
Rank#19  Overall
#13  Relational DBMS
Score27.71
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score1.49
Rank#155  Overall
#72  Relational DBMS
Websitecloud.google.com/­bigqueryazure.microsoft.com/­services/­cosmos-dbplanetscale.com
Technical documentationcloud.google.com/­bigquery/­docslearn.microsoft.com/­azure/­cosmos-dbplanetscale.com/­docs
DeveloperGoogleMicrosoftPlanetScale
Initial release201020142020
License infoCommercial or Open Sourcecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGo
Server operating systemshostedhostedDocker
Linux
macOS
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes infoJSON typesyes
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.no
Secondary indexesnoyes infoAll properties auto-indexed by defaultyes
SQL infoSupport of SQLyesSQL-like query languageyes infowith proprietary extensions
APIs and other access methodsRESTful HTTP/JSON APIDocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
ADO.NET
JDBC
MySQL protocol
ODBC
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
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptJavaScriptyes infoproprietary syntax
TriggersnoJavaScriptyes
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 serviceMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*no
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 across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engine
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 partitionACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engine
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
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 levelUsers with fine-grained authorization concept infono user groups or roles

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More resources
Google BigQueryMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBPlanetScale
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