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DBMS > DataFS vs. Google Cloud Datastore vs. RavenDB vs. Teradata

System Properties Comparison DataFS vs. Google Cloud Datastore vs. RavenDB vs. Teradata

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Editorial information provided by DB-Engines
NameDataFS  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRavenDB  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelObject oriented DBMSDocument storeDocument storeRelational DBMS
Secondary database modelsGraph DBMSGraph DBMS
Spatial DBMS
Time Series DBMS
Document store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score2.92
Rank#101  Overall
#18  Document stores
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitenewdatabase.comcloud.google.com/­datastoreravendb.netwww.teradata.com
Technical documentationdev.mobiland.com/­Overview.xspcloud.google.com/­datastore/­docsravendb.net/­docsdocs.teradata.com
DeveloperMobiland AGGoogleHibernating RhinosTeradata
Initial release2018200820101984
Current release1.1.263, October 20225.4, July 2022Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL version 3, commercial license availablecommercial
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#
Server operating systemsWindowshostedLinux
macOS
Raspberry Pi
Windows
hosted
Linux
Data schemeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details herenoyes
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.nonoyes
Secondary indexesnoyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like query language (RQL)yes infoSQL 2016 + extensions
APIs and other access methods.NET Client API
Proprietary client DLL
WinRT client
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languages.Net
C
C#
C++
VB.Net
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresusing Google App Engineyesyes infoUDFs, stored procedures, table functions in parallel
Triggersno, except callback-events from server when changes happenedCallbacks using the Google Apps Engineyesyes
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemShardingShardingSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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.Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID, Cluster-wide transaction availableACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlWindows-ProfileAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Authorization levels configured per client per databasefine grained access rights according to SQL-standard

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More resources
DataFSGoogle Cloud DatastoreRavenDBTeradata
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