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DBMS > FatDB vs. Google Cloud Datastore vs. Microsoft Access vs. Titan

System Properties Comparison FatDB vs. Google Cloud Datastore vs. Microsoft Access vs. Titan

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonTitan  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMicrosoft 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.)Titan is a Graph DBMS optimized for distributed clusters.
Primary database modelDocument store
Key-value store
Document storeRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#71  Overall
#12  Document stores
Score93.76
Rank#12  Overall
#8  Relational DBMS
Websitecloud.google.com/­datastorewww.microsoft.com/­en-us/­microsoft-365/­accessgithub.com/­thinkaurelius/­titan
Technical documentationcloud.google.com/­datastore/­docsdeveloper.microsoft.com/­en-us/­accessgithub.com/­thinkaurelius/­titan/­wiki
DeveloperFatCloudGoogleMicrosoftAurelius, owned by DataStax
Initial release2012200819922012
Current release1902 (16.0.11328.20222), March 2019
License infoCommercial or Open Sourcecommercialcommercialcommercial infoBundled with Microsoft OfficeOpen Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#C++Java
Server operating systemsWindowshostedWindows infoNot a real database server, but making use of DLLsLinux
OS X
Unix
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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.no
Secondary indexesyesyesyesyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like query language (GQL)yes infobut not compliant to any SQL standardno
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
ADO.NET
DAO
ODBC
OLE DB
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesC#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Clojure
Java
Python
Server-side scripts infoStored proceduresyes infovia applicationsusing Google App Engineyes infosince Access 2010 using the ACE-engineyes
Triggersyes infovia applicationsCallbacks using the Google Apps Engineyes infosince Access 2010 using the ACE-engineyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using Paxosnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflownoyes infovia Faunus, a graph analytics engine
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 Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infobut no files for transaction loggingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
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)no infoa simple user-level security was built in till version Access 2003User authentification and security via Rexster Graph Server

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More resources
FatDBGoogle Cloud DatastoreMicrosoft AccessTitan
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