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DBMS > FatDB vs. Google Cloud Datastore vs. Solr vs. TinkerGraph vs. Warp 10

System Properties Comparison FatDB vs. Google Cloud Datastore vs. Solr vs. TinkerGraph vs. Warp 10

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSolr  Xexclude from comparisonTinkerGraph  Xexclude from comparisonWarp 10  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 LuceneA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 APITimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelDocument store
Key-value store
Document storeSearch engineGraph DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score41.02
Rank#24  Overall
#3  Search engines
Score0.13
Rank#345  Overall
#35  Graph DBMS
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websitecloud.google.com/­datastoresolr.apache.orgtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlinwww.warp10.io
Technical documentationcloud.google.com/­datastore/­docssolr.apache.org/­resources.htmlwww.warp10.io/­content/­02_Getting_started
DeveloperFatCloudGoogleApache Software FoundationSenX
Initial release20122008200620092015
Current release9.6.1, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#JavaJavaJava
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 fieldsschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes, details hereyes infosupports customizable data types and automatic typingyesyes
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.noyesnono
Secondary indexesyesyesyes infoAll search fields are automatically indexednono
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like query language (GQL)Solr Parallel SQL Interfacenono
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
TinkerPop 3HTTP API
Jupyter
WebSocket
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
Groovy
Java
Server-side scripts infoStored proceduresyes infovia applicationsusing Google App EngineJava pluginsnoyes infoWarpScript
Triggersyes infovia applicationsCallbacks using the Google Apps Engineyes infoUser configurable commands triggered on index changesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnoneSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using Paxosyesnoneselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflowspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenono
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 ConsistencynoneImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsoptimistic lockingnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesnoyes
Durability infoSupport for making data persistentyesyesyesoptionalyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
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)yesnoMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
FatDBGoogle Cloud DatastoreSolrTinkerGraphWarp 10
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