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DBMS > Amazon Neptune vs. Amazon SimpleDB vs. Microsoft Access vs. Solr

System Properties Comparison Amazon Neptune vs. Amazon SimpleDB vs. Microsoft Access vs. Solr

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonAmazon SimpleDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSolr  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 widely used distributed, scalable search engine based on Apache Lucene
Primary database modelGraph DBMS
RDF store
Key-value storeRelational DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.82
Rank#109  Overall
#9  Graph DBMS
#5  RDF stores
Score1.90
Rank#145  Overall
#24  Key-value stores
Score107.93
Rank#11  Overall
#8  Relational DBMS
Score43.91
Rank#24  Overall
#3  Search engines
Websiteaws.amazon.com/­neptuneaws.amazon.com/­simpledbwww.microsoft.com/­en-us/­microsoft-365/­accesssolr.apache.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.aws.amazon.com/­simpledbdeveloper.microsoft.com/­en-us/­accesssolr.apache.org/­resources.html
DeveloperAmazonAmazonMicrosoftApache Software Foundation
Initial release2017200719922006
Current release1902 (16.0.11328.20222), March 20199.5.0, February 2024
License infoCommercial or Open Sourcecommercialcommercialcommercial infoBundled with Microsoft OfficeOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemshostedhostedWindows infoNot a real database server, but making use of DLLsAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesnoyesyes infosupports customizable data types and automatic typing
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
Secondary indexesnoyes infoAll columns are indexed automaticallyyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnonoyes infobut not compliant to any SQL standardSolr Parallel SQL Interface
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
RESTful HTTP APIADO.NET
DAO
ODBC
OLE DB
Java API
RESTful HTTP/JSON API
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
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnonoyes infosince Access 2010 using the ACE-engineJava plugins
Triggersnonoyes infosince Access 2010 using the ACE-engineyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnonenone infoSharding must be implemented in the applicationnoneSharding
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.yesnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyesno
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 loggingoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
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 2003yes

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More resources
Amazon NeptuneAmazon SimpleDBMicrosoft AccessSolr
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