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DBMS > Amazon Neptune vs. FatDB vs. NCache vs. Spark SQL

System Properties Comparison Amazon Neptune vs. FatDB vs. NCache vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonFatDB  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.
DescriptionFast, reliable graph database built for the cloudA .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 processing
Primary database modelGraph DBMS
RDF store
Document store
Key-value store
Key-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
Score2.58
Rank#112  Overall
#9  Graph DBMS
#5  RDF stores
Score0.98
Rank#196  Overall
#29  Key-value stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptunewww.alachisoft.com/­ncachespark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.alachisoft.com/­resources/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonFatCloudAlachisoftApache Software Foundation
Initial release2017201220052014
Current release5.3.3, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoEnterprise Edition availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#C#, .NET, .NET Core, JavaScala
Server operating systemshostedWindowsLinux
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyespartial 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 indexesnoyesyesno
SQL infoSupport of SQLnono 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 statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
IDistributedCache
JCache
LINQ
Proprietary native API
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C#.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infovia applicationsno infosupport for stored procedures with SQL-Server CLRno
Triggersnoyes infovia applicationsyes infoNotificationsno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyesyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.selectable replication factoryes, with selectable consistency levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology
Foreign keys infoReferential integrityyes infoRelationships in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic locking and pessimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)no infoCan implement custom security layer via applicationsAuthentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)no
More information provided by the system vendor
Amazon NeptuneFatDBNCacheSpark 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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Amazon NeptuneFatDBNCacheSpark SQL
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