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DBMS > Drizzle vs. FatDB vs. Google Cloud Firestore vs. Kinetica vs. searchxml

System Properties Comparison Drizzle vs. FatDB vs. Google Cloud Firestore vs. Kinetica vs. searchxml

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonKinetica  Xexclude from comparisonsearchxml  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A .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 CPUsDBMS for structured and unstructured content wrapped with an application server
Primary database modelRelational DBMSDocument store
Key-value store
Document storeRelational DBMSNative XML DBMS
Search engine
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
Score0.03
Rank#390  Overall
#7  Native XML DBMS
#24  Search engines
Websitefirebase.google.com/­products/­firestorewww.kinetica.comwww.searchxml.net/­category/­products
Technical documentationfirebase.google.com/­docs/­firestoredocs.kinetica.comwww.searchxml.net/­support/­handouts
DeveloperDrizzle project, originally started by Brian AkerFatCloudGoogleKineticainformationpartners gmbh
Initial release20082012201720122015
Current release7.2.4, September 20127.1, August 20211.0
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C#C, C++C++
Server operating systemsFreeBSD
Linux
OS X
WindowshostedLinuxWindows
Data schemeyesschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 indexesyesyesyesyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsno infoVia inetgration in SQL ServernoSQL-like DML and DDL statementsno
APIs and other access methodsJDBC.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
RESTful HTTP API
WebDAV
XQuery
XSLT
Supported programming languagesC
C++
Java
PHP
C#Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++
Java
JavaScript (Node.js)
Python
C++ infomost other programming languages supported via APIs
Server-side scripts infoStored proceduresnoyes infovia applicationsyes, Firebase Rules & Cloud Functionsuser defined functionsyes infoon the application server
Triggersno infohooks for callbacks inside the server can be used.yes infovia applicationsyes, with Cloud Functionsyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factorMulti-source replicationSource-replica replicationyes infosychronisation to multiple collections
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesUsing Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyesnomultiple readers, single writer
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMno
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPno 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 levelDomain, group and role-based access control at the document level and for application services

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More resources
DrizzleFatDBGoogle Cloud FirestoreKineticasearchxml
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