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DBMS > Google Cloud Bigtable vs. Microsoft Access vs. Microsoft Azure Table Storage vs. Tigris

System Properties Comparison Google Cloud Bigtable vs. Microsoft Access vs. Microsoft Azure Table Storage vs. Tigris

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonTigris  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Microsoft 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.)A Wide Column Store for rapid development using massive semi-structured datasetsA horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelKey-value store
Wide column store
Relational DBMSWide column storeDocument store
Key-value store
Search engine
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.02
Rank#369  Overall
#51  Document stores
#55  Key-value stores
#24  Search engines
#38  Time Series DBMS
Websitecloud.google.com/­bigtablewww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­en-us/­services/­storage/­tableswww.tigrisdata.com
Technical documentationcloud.google.com/­bigtable/­docsdeveloper.microsoft.com/­en-us/­accesswww.tigrisdata.com/­docs
DeveloperGoogleMicrosoftMicrosoftTigris Data, Inc.
Initial release2015199220122022
Current release1902 (16.0.11328.20222), March 2019
License infoCommercial or Open Sourcecommercialcommercial infoBundled with Microsoft OfficecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemshostedWindows infoNot a real database server, but making use of DLLshostedLinux
macOS
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesyesyes
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.nonono
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoyes infobut not compliant to any SQL standardnono
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
DAO
ODBC
OLE DB
RESTful HTTP APICLI Client
gRPC
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Server-side scripts infoStored proceduresnoyes infosince Access 2010 using the ACE-enginenono
Triggersnoyes infosince Access 2010 using the ACE-enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesnoneyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACID infobut no files for transaction loggingoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infobut no files for transaction loggingyesyes, using FoundationDB
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 based on Google Cloud Identity and Access Management (IAM)no infoa simple user-level security was built in till version Access 2003Access rights based on private key authentication or shared access signaturesAccess rights for users and roles

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More resources
Google Cloud BigtableMicrosoft AccessMicrosoft Azure Table StorageTigris
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