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

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

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphGoogle'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 datasets
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Key-value store
Wide column store
Relational DBMSWide column store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
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
Websitebangdb.comcloud.google.com/­bigtablewww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationdocs.bangdb.comcloud.google.com/­bigtable/­docsdeveloper.microsoft.com/­en-us/­access
DeveloperSachin Sinha, BangDBGoogleMicrosoftMicrosoft
Initial release2012201519922012
Current releaseBangDB 2.0, October 20211902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoBSD 3commercialcommercial infoBundled with Microsoft Officecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C++
Server operating systemsLinuxhostedWindows infoNot a real database server, but making use of DLLshosted
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsnoyesyes
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 indexesyes infosecondary, composite, nested, reverse, geospatialnoyesno
SQL infoSupport of SQLSQL like support with command line toolnoyes infobut not compliant to any SQL standardno
APIs and other access methodsProprietary protocol
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
DAO
ODBC
OLE DB
RESTful HTTP API
Supported programming languagesC
C#
C++
Java
Python
C#
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
Server-side scripts infoStored proceduresnonoyes infosince Access 2010 using the ACE-engineno
Triggersyes, Notifications (with Streaming only)noyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Internal 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.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACID infobut no files for transaction loggingoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyes 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.yes, run db with in-memory only modenono
User concepts infoAccess controlyes (enterprise version only)Access 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 signatures

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More resources
BangdbGoogle Cloud BigtableMicrosoft AccessMicrosoft Azure Table Storage
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