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DBMS > FatDB vs. NCache vs. Riak TS vs. Spark SQL

System Properties Comparison FatDB vs. NCache vs. Riak TS vs. Spark SQL

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonNCache  Xexclude from comparisonRiak TS  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.Open-Source and Enterprise in-memory Key-Value StoreRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KVSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Key-value storeTime Series DBMSRelational 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#195  Overall
#29  Key-value stores
Score0.20
Rank#319  Overall
#27  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.alachisoft.com/­ncachespark.apache.org/­sql
Technical documentationwww.alachisoft.com/­resources/­docswww.tiot.jp/­riak-docs/­riak/­ts/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudAlachisoftOpen Source, formerly Basho TechnologiesApache Software Foundation
Initial release2012200520152014
Current release5.3.3, April 20243.0.0, September 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoEnterprise Edition availableOpen SourceOpen 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#, .NET, .NET Core, JavaErlangScala
Server operating systemsWindowsLinux
Windows
Linux
OS X
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyespartial infoSupported data types are Lists, Queues, Hashsets, Dictionary and Counternoyes
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 indexesyesyesrestrictedno
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.yes, limitedSQL-like DML and DDL statements
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
IDistributedCache
JCache
LINQ
Proprietary native API
HTTP API
Native Erlang Interface
JDBC
ODBC
Supported programming languagesC#.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsno infosupport for stored procedures with SQL-Server CLRErlangno
Triggersyes infovia applicationsyes infoNotificationsyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingyesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes, with selectable consistency levelselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes
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
Eventual Consistency
Foreign keys infoReferential integritynonono infolinks between datasets can be storedno
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
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
FatDBNCacheRiak TSSpark 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
FatDBNCacheRiak TSSpark SQL
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