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DBMS > DataFS vs. Google Cloud Datastore vs. Kinetica vs. WakandaDB

System Properties Comparison DataFS vs. Google Cloud Datastore vs. Kinetica vs. WakandaDB

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Editorial information provided by DB-Engines
NameDataFS  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonWakandaDB  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 PlatformFully vectorized database across both GPUs and CPUsWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelObject oriented DBMSDocument storeRelational DBMSObject oriented DBMS
Secondary database modelsGraph DBMSSpatial 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
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitenewdatabase.comcloud.google.com/­datastorewww.kinetica.comwakanda.github.io
Technical documentationdev.mobiland.com/­Overview.xspcloud.google.com/­datastore/­docsdocs.kinetica.comwakanda.github.io/­doc
DeveloperMobiland AGGoogleKineticaWakanda SAS
Initial release2018200820122012
Current release1.1.263, October 20227.1, August 20212.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoAGPLv3, extended commercial license available
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++C++, JavaScript
Server operating systemsWindowshostedLinuxLinux
OS X
Windows
Data schemeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-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.nononono
Secondary indexesnoyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like DML and DDL statementsno
APIs and other access methods.NET Client API
Proprietary client DLL
WinRT client
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languages.Net
C
C#
C++
VB.Net
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
JavaScript
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsyes
Triggersno, except callback-events from server when changes happenedCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
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.Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
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 infoGPU vRAM or System RAMno
User concepts infoAccess controlWindows-ProfileAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelyes

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More resources
DataFSGoogle Cloud DatastoreKineticaWakandaDB
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