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

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

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonRavenDB  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 Operational and Transactional Enterprise NoSQL Document 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 DBMSDocument storeDocument storeRelational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series 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
Score2.92
Rank#101  Overall
#18  Document stores
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/­accessravendb.netrealm.iospark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdeveloper.microsoft.com/­en-us/­accessravendb.net/­docsrealm.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonMicrosoftHibernating RhinosRealm, acquired by MongoDB in May 2019Apache Software Foundation
Initial release20171992201020142014
Current release1902 (16.0.11328.20222), March 20195.4, July 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infoBundled with Microsoft OfficeOpen Source infoAGPL version 3, commercial license availableOpen 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 DLLsLinux
macOS
Raspberry Pi
Windows
Android
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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 indexesnoyesyesyesno
SQL infoSupport of SQLnoyes infobut not compliant to any SQL standardSQL-like query language (RQL)noSQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
DAO
ODBC
OLE DB
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
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-engineyesno inforuns within the applications so server-side scripts are unnecessaryno
Triggersnoyes infosince Access 2010 using the ACE-engineyesyes 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.noneMulti-source replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate 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 loggingACID, Cluster-wide transaction availableACIDno
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.yes 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 2003Authorization levels configured per client per databaseyesno

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More resources
Amazon NeptuneMicrosoft AccessRavenDBRealmSpark SQL
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