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

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

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonQuasardb  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.)Distributed, high-performance timeseries databaseA 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
Score0.14
Rank#332  Overall
#29  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/­accessquasar.airealm.iospark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdeveloper.microsoft.com/­en-us/­accessdoc.quasar.ai/­masterrealm.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonMicrosoftquasardbRealm, acquired by MongoDB in May 2019Apache Software Foundation
Initial release20171992200920142014
Current release1902 (16.0.11328.20222), March 20193.14.1, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infoBundled with Microsoft Officecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++Scala
Server operating systemshostedWindows infoNot a real database server, but making use of DLLsBSD
Linux
OS X
Windows
Android
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes infointeger and binaryyesyes
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.nononono
Secondary indexesnoyesyes infowith tagsyesno
SQL infoSupport of SQLnoyes infobut not compliant to any SQL standardSQL-like query languagenoSQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
DAO
ODBC
OLE DB
HTTP 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
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.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 nodesnonenoneSharding infoconsistent hashingnoneyes, 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.noneSource-replica replication with selectable replication factornonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonowith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate 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 loggingACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyes infobut no files for transaction loggingyes infoby using LevelDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoTransient modeyes 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 2003Cryptographically strong user authentication and audit trailyesno

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More resources
Amazon NeptuneMicrosoft AccessQuasardbRealmSpark SQL
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