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DBMS > FatDB vs. Google Cloud Datastore vs. Solr vs. Valentina Server

System Properties Comparison FatDB vs. Google Cloud Datastore vs. Solr vs. Valentina Server

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSolr  Xexclude from comparisonValentina Server  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA widely used distributed, scalable search engine based on Apache LuceneObject-relational database and reports server
Primary database modelDocument store
Key-value store
Document storeSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score42.91
Rank#24  Overall
#3  Search engines
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitecloud.google.com/­datastoresolr.apache.orgwww.valentina-db.net
Technical documentationcloud.google.com/­datastore/­docssolr.apache.org/­resources.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperFatCloudGoogleApache Software FoundationParadigma Software
Initial release2012200820061999
Current release9.6.0, April 20245.7.5
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2commercial
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#Java
Server operating systemsWindowshostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeschema-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes, details hereyes infosupports customizable data types and automatic typingyes
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.noyes
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like query language (GQL)Solr Parallel SQL Interfaceyes
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
Java API
RESTful HTTP/JSON API
ODBC
Supported programming languagesC#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresyes infovia applicationsusing Google App EngineJava pluginsyes
Triggersyes infovia applicationsCallbacks using the Google Apps Engineyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using Paxosyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflowspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
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
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsoptimistic locking
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.noyesyes
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)yesfine grained access rights according to SQL-standard

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More resources
FatDBGoogle Cloud DatastoreSolrValentina Server
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