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DBMS > FatDB vs. NCache vs. Spark SQL vs. Sphinx

System Properties Comparison FatDB vs. NCache vs. Spark SQL vs. Sphinx

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonNCache  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  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.Open-Source and Enterprise in-memory Key-Value StoreSpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Key-value store
Key-value storeRelational DBMSSearch engine
Secondary database modelsDocument store
Search engine infoUsing distributed Lucene
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.94
Rank#195  Overall
#29  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.alachisoft.com/­ncachespark.apache.org/­sqlsphinxsearch.com
Technical documentationwww.alachisoft.com/­resources/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperFatCloudAlachisoftApache Software FoundationSphinx Technologies Inc.
Initial release2012200520142001
Current release5.3.3, April 20243.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoEnterprise Edition availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#C#, .NET, .NET Core, JavaScalaC++
Server operating systemsWindowsLinux
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyespartial infoSupported data types are Lists, Queues, Hashsets, Dictionary and Counteryesno
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.nono
Secondary indexesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.SQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
IDistributedCache
JCache
LINQ
Proprietary native API
JDBC
ODBC
Proprietary protocol
Supported programming languagesC#.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes infovia applicationsno infosupport for stored procedures with SQL-Server CLRnono
Triggersyes infovia applicationsyes infoNotificationsnono
Partitioning methods infoMethods for storing different data on different nodesShardingyesyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes, with selectable consistency levelnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic locking and pessimistic lockingnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAuthentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)nono
More information provided by the system vendor
FatDBNCacheSpark SQLSphinx
Specific characteristicsNCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more
Competitive advantagesNCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more
Typical application scenariosNCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more
Key customersBank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more
Market metricsMarket Leader in .NET Distributed Caching since 2005.
» more
Licensing and pricing modelsNCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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FatDBNCacheSpark SQLSphinx
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