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DBMS > Amazon Neptune vs. Amazon SimpleDB vs. Microsoft Access vs. Realm vs. Spark SQL

System Properties Comparison Amazon Neptune vs. Amazon SimpleDB vs. Microsoft Access vs. Realm vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonAmazon SimpleDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonRealm  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Key-value storeRelational DBMSDocument storeRelational 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
Score1.85
Rank#138  Overall
#24  Key-value stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptuneaws.amazon.com/­simpledbwww.microsoft.com/­en-us/­microsoft-365/­accessrealm.iospark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.aws.amazon.com/­simpledbdeveloper.microsoft.com/­en-us/­accessrealm.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonAmazonMicrosoftRealm, acquired by MongoDB in May 2019Apache Software Foundation
Initial release20172007199220142014
Current release1902 (16.0.11328.20222), March 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infoBundled with Microsoft OfficeOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Scala
Server operating systemshostedhostedWindows infoNot a real database server, but making use of DLLsAndroid
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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 indexesnoyes infoAll columns are indexed automaticallyyesyesno
SQL infoSupport of SQLnonoyes infobut not compliant to any SQL standardnoSQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
RESTful HTTP APIADO.NET
DAO
ODBC
OLE DB
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
Java infowith Android only
Objective-C
React Native
Swift
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes infosince Access 2010 using the ACE-engineno inforuns within the applications so server-side scripts are unnecessaryno
Triggersnonoyes infosince Access 2010 using the ACE-engineyes infoChange Listenersno
Partitioning methods infoMethods for storing different data on different nodesnonenone infoSharding must be implemented in the applicationnonenoneyes, 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.yesnonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoConcurrent data updates can be detected by the applicationACID infobut no files for transaction loggingACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes infobut no files for transaction loggingyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoIn-Memory realmno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)no infoa simple user-level security was built in till version Access 2003yesno

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More resources
Amazon NeptuneAmazon SimpleDBMicrosoft AccessRealmSpark SQL
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