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DBMS > FatDB vs. Google Cloud Firestore vs. Kinetica vs. Oracle Berkeley DB

System Properties Comparison FatDB vs. Google Cloud Firestore vs. Kinetica vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonKinetica  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Fully vectorized database across both GPUs and CPUsWidely used in-process key-value store
Primary database modelDocument store
Key-value store
Document storeRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.36
Rank#53  Overall
#9  Document stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Websitefirebase.google.com/­products/­firestorewww.kinetica.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationfirebase.google.com/­docs/­firestoredocs.kinetica.comdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperFatCloudGoogleKineticaOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release2012201720121994
Current release7.1, August 202118.1.40, May 2020
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#C, C++C, Java, C++ (depending on the Berkeley DB edition)
Server operating systemsWindowshostedLinuxAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 infoonly with the Berkeley DB XML edition
Secondary indexesyesyesyesyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServernoSQL-like DML and DDL statementsyes infoSQL interfaced based on SQLite is available
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++
Java
JavaScript (Node.js)
Python
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresyes infovia applicationsyes, Firebase Rules & Cloud Functionsuser defined functionsno
Triggersyes infovia applicationsyes, with Cloud Functionsyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replicationSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesUsing Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yes infoGPU vRAM or System RAMyes
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. Security Rules for 3rd party authentication using Firebase Auth.Access rights for users and roles on table levelno

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More resources
FatDBGoogle Cloud FirestoreKineticaOracle Berkeley DB
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