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

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

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHyprcubd  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonTrino  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.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 datasetsFast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL
Primary database modelDocument store
Key-value store
Document storeTime Series DBMSWide column storeRelational DBMS
Secondary database modelsDocument store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#71  Overall
#12  Document stores
Score3.55
Rank#80  Overall
#6  Wide column stores
Score5.28
Rank#61  Overall
#35  Relational DBMS
Websitecloud.google.com/­datastorehyprcubd.com (offline)azure.microsoft.com/­en-us/­services/­storage/­tablestrino.io
Technical documentationcloud.google.com/­datastore/­docstrino.io/­broadcast
trino.io/­docs/­current
DeveloperFatCloudGoogleHyprcubd, Inc.MicrosoftTrino Software Foundation
Initial release2012200820122012 info2020 rebranded from PrestoSQL
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#GoJava
Server operating systemsWindowshostedhostedhostedLinux
macOS infofor devlopment
Data schemeschema-freeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details hereyes infotime, int, uint, float, stringyesyes
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.nononono
Secondary indexesyesyesnonodepending on connected data-source
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like query language (GQL)SQL-like query languagenoyes
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
gRPC (https)RESTful HTTP APIJDBC
RESTful HTTP API
Trino CLI
Supported programming languagesC#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
R
Ruby
Server-side scripts infoStored proceduresyes infovia applicationsusing Google App Enginenonoyes, depending on connected data-source
Triggersyes infovia applicationsCallbacks using the Google Apps Enginenonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicedepending on connected data-source
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using Paxosyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.depending on connected data-source
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate 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 Consistencydepending on connected data-source
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnooptimistic lockingdepending on connected data-source
Concurrency infoSupport for concurrent manipulation of datayesyesnoyesyes
Durability infoSupport for making data persistentyesyesyesyesdepending on connected data-source
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 applicationsAccess 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 signaturesSQL standard access control
More information provided by the system vendor
FatDBGoogle Cloud DatastoreHyprcubdMicrosoft Azure Table StorageTrino
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More resources
FatDBGoogle Cloud DatastoreHyprcubdMicrosoft Azure Table StorageTrino
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