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

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

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonPrometheus  Xexclude from comparisonRealm  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudMicrosoft 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.)Open-source Time Series DBMS and monitoring systemA 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
Relational DBMSTime Series 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
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptunewww.microsoft.com/­en-us/­microsoft-365/­accessprometheus.iorealm.iospark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdeveloper.microsoft.com/­en-us/­accessprometheus.io/­docsrealm.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonMicrosoftRealm, acquired by MongoDB in May 2019Apache Software Foundation
Initial release20171992201520142014
Current release1902 (16.0.11328.20222), March 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infoBundled with Microsoft OfficeOpen Source infoApache 2.0Open SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++GoScala
Server operating systemshostedWindows infoNot a real database server, but making use of DLLsLinux
Windows
Android
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesNumeric data onlyyesyes
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 infoImport of XML data possiblenono
Secondary indexesnoyesnoyesno
SQL infoSupport of SQLnoyes infobut not compliant to any SQL standardnonoSQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
DAO
ODBC
OLE DB
RESTful HTTP/JSON APIJDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
.Net
Java infowith Android only
Objective-C
React Native
Swift
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infosince Access 2010 using the ACE-enginenono inforuns within the applications so server-side scripts are unnecessaryno
Triggersnoyes infosince Access 2010 using the ACE-enginenoyes infoChange Listenersno
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingnoneyes, 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.noneyes infoby Federationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infobut no files for transaction loggingnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyes infobut no files for transaction loggingyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoIn-Memory realmno
User concepts infoAccess controlAccess 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 2003noyesno

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More resources
Amazon NeptuneMicrosoft AccessPrometheusRealmSpark SQL
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