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

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

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonFatDB  Xexclude from comparisonIngres  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.Well established RDBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Document store
Key-value store
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptunewww.actian.com/­databases/­ingresspark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.actian.com/­ingresspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonFatCloudActian CorporationApache Software Foundation
Initial release201720121974 infooriginally developed at University Berkely in early 1970s2014
Current release11.2, May 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen 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#CScala
Server operating systemshostedWindowsAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesnoyesyesno
SQL infoSupport of SQLnono infoVia inetgration in SQL ServeryesSQL-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
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C#Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infovia applicationsyesno
Triggersnoyes infovia applicationsyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslyyes, 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 factorIngres Replicatornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyes
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.nono
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 applicationsfine grained access rights according to SQL-standardno

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More resources
Amazon NeptuneFatDBIngresSpark SQL
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