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DBMS > FatDB vs. GBase vs. Google Cloud Datastore vs. Hyprcubd vs. Microsoft Azure Table Storage

System Properties Comparison FatDB vs. GBase vs. Google Cloud Datastore vs. Hyprcubd vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGBase  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHyprcubd  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformServerless Time Series DBMSA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelDocument store
Key-value store
Relational DBMSDocument storeTime Series DBMSWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.11
Rank#173  Overall
#78  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score3.55
Rank#80  Overall
#6  Wide column stores
Websitewww.gbase.cncloud.google.com/­datastorehyprcubd.com (offline)azure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationcloud.google.com/­datastore/­docs
DeveloperFatCloudGeneral Data Technology Co., Ltd.GoogleHyprcubd, Inc.Microsoft
Initial release2012200420082012
Current releaseGBase 8a, GBase 8s, GBase 8c
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#C, Java, PythonGo
Server operating systemsWindowsLinuxhostedhostedhosted
Data schemeschema-freeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereyes infotime, int, uint, float, stringyes
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.yesnonono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLno infoVia inetgration in SQL ServerStandard with numerous extensionsSQL-like query language (GQL)SQL-like query languageno
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
ADO.NET
C API
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
gRPC (https)RESTful HTTP API
Supported programming languagesC#C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infovia applicationsuser defined functionsusing Google App Enginenono
Triggersyes infovia applicationsyesCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by range, list and hash) and vertical partitioningShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication using Paxosyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesnoyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)token accessAccess rights based on private key authentication or shared access signatures

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More resources
FatDBGBaseGoogle Cloud DatastoreHyprcubdMicrosoft Azure Table Storage
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