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

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

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonKeyDB  Xexclude from comparisonNCache  Xexclude from comparisonSpark SQL  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.An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsOpen-Source and Enterprise in-memory Key-Value StoreSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Key-value storeKey-value storeRelational DBMS
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#205  Overall
#30  Key-value stores
Score1.21
Rank#181  Overall
#29  Key-value stores
Score19.56
Rank#34  Overall
#21  Relational DBMS
Websitegithub.com/­Snapchat/­KeyDB
keydb.dev
www.alachisoft.com/­ncachespark.apache.org/­sql
Technical documentationdocs.keydb.devwww.alachisoft.com/­resources/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudEQ Alpha Technology Ltd.AlachisoftApache Software Foundation
Initial release2012201920052014
Current release5.3, September 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSD-3Open Source infoEnterprise Edition availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#C++C#, .NET, .NET Core, JavaScala
Server operating systemsWindowsLinuxLinux
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexespartial infoSupported data types are Lists, Queues, Hashsets, Dictionary and Counteryes
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.nonono
Secondary indexesyesyes infoby using the Redis Search moduleyesno
SQL infoSupport of SQLno infoVia inetgration in SQL ServernoSQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.SQL-like DML and DDL statements
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Proprietary protocol infoRESP - REdis Serialization ProtocoIDistributedCache
JCache
LINQ
Proprietary native API
JDBC
ODBC
Supported programming languagesC#C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsLuano infosupport for stored procedures with SQL-Server CLRno
Triggersyes infovia applicationsnoyes infoNotificationsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyesyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
yes, with selectable consistency levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual Consistency
Strong eventual consistency with CRDTs
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, atomic execution of commands blocks and scriptsoptimistic locking and pessimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlno infoCan implement custom security layer via applicationssimple password-based access control and ACLAuthentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)no
More information provided by the system vendor
FatDBKeyDBNCacheSpark SQL
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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More resources
FatDBKeyDBNCacheSpark SQL
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