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DBMS > Google BigQuery vs. IBM Cloudant vs. Microsoft Access vs. Microsoft Azure Cosmos DB

System Properties Comparison Google BigQuery vs. IBM Cloudant vs. Microsoft Access vs. Microsoft Azure Cosmos DB

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonIBM Cloudant  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesDatabase as a Service offering based on Apache CouchDBMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Globally distributed, horizontally scalable, multi-model database service
Primary database modelRelational DBMSDocument storeRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score62.67
Rank#19  Overall
#13  Relational DBMS
Score2.79
Rank#113  Overall
#21  Document stores
Score107.93
Rank#11  Overall
#8  Relational DBMS
Score30.39
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Websitecloud.google.com/­bigquerywww.ibm.com/­products/­cloudantwww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­services/­cosmos-db
Technical documentationcloud.google.com/­bigquery/­docscloud.ibm.com/­docs/­Cloudantdeveloper.microsoft.com/­en-us/­accesslearn.microsoft.com/­azure/­cosmos-db
DeveloperGoogleIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014MicrosoftMicrosoft
Initial release2010201019922014
Current release1902 (16.0.11328.20222), March 2019
License infoCommercial or Open Sourcecommercialcommercialcommercial infoBundled with Microsoft Officecommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangC++
Server operating systemshostedhostedWindows infoNot a real database server, but making use of DLLshosted
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyes infoJSON types
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 indexesnoyesyesyes infoAll properties auto-indexed by default
SQL infoSupport of SQLyesnoyes infobut not compliant to any SQL standardSQL-like query language
APIs and other access methodsRESTful HTTP/JSON APIRESTful HTTP/JSON APIADO.NET
DAO
ODBC
OLE DB
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C#
Java
JavaScript
Objective-C
PHP
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptView functions (Map-Reduce) in JavaScriptyes infosince Access 2010 using the ACE-engineJavaScript
Triggersnoyesyes infosince Access 2010 using the ACE-engineJavaScript
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnowith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying datano infoatomic operations within a document possibleACID infobut no files for transaction loggingMulti-item ACID transactions with snapshot isolation within a partition
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic lockingyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyes
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)Access rights for users can be defined per databaseno infoa simple user-level security was built in till version Access 2003Access rights can be defined down to the item level

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More resources
Google BigQueryIBM CloudantMicrosoft AccessMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB
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