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DBMS > Amazon Neptune vs. FileMaker vs. Microsoft Azure Table Storage vs. Spark SQL

System Properties Comparison Amazon Neptune vs. FileMaker vs. Microsoft Azure Table Storage vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonFileMaker  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudFileMaker is a cross-platform RDBMS that includes a GUI frontend.A Wide Column Store for rapid development using massive semi-structured datasetsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Relational DBMSWide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score47.91
Rank#20  Overall
#14  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptunewww.claris.com/­filemakerazure.microsoft.com/­en-us/­services/­storage/­tablesspark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.claris.com/­resources/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonClaris infoa subsidiary of AppleMicrosoftApache Software Foundation
Initial release2017198320122014
Current release19.4.1, November 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScala
Server operating systemshostediOS infoclient part only
Linux
OS X
Windows
hostedLinux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
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.noyes infoA http query request can return the data in XML formatnono
Secondary indexesnoyesnono
SQL infoSupport of SQLnoyes infovia pluginsnoSQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Filemaker WebDirect
JDBC
ODBC
RESTful HTTP APIJDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
PHP.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesnono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding infoImplicit feature of the cloud serviceyes, 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.Source-replica replication, warm standby infosince Version 14yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic 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.nono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)simple rights management via user accounts and connection to external directory servicesAccess rights based on private key authentication or shared access signaturesno

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More resources
Amazon NeptuneFileMakerMicrosoft Azure Table StorageSpark SQL
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