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DBMS > Amazon Neptune vs. FatDB vs. Solr vs. TimescaleDB

System Properties Comparison Amazon Neptune vs. FatDB vs. Solr vs. TimescaleDB

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonFatDB  Xexclude from comparisonSolr  Xexclude from comparisonTimescaleDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionFast, reliable graph database built for the cloudA .NET NoSQL DBMS that can integrate with and extend SQL Server.A widely used distributed, scalable search engine based on Apache LuceneA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelGraph DBMS
RDF store
Document store
Key-value store
Search engineTime Series DBMS
Secondary database modelsSpatial DBMSRelational 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
Score42.91
Rank#24  Overall
#3  Search engines
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websiteaws.amazon.com/­neptunesolr.apache.orgwww.timescale.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcessolr.apache.org/­resources.htmldocs.timescale.com
DeveloperAmazonFatCloudApache Software FoundationTimescale
Initial release2017201220062017
Current release9.5.0, February 20242.13.0, November 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#JavaC
Server operating systemshostedWindowsAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeschema-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.noyesyes
Secondary indexesnoyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnono infoVia inetgration in SQL ServerSolr Parallel SQL Interfaceyes infofull PostgreSQL SQL syntax
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C#.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyes infovia applicationsJava pluginsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyes infovia applicationsyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes, across time and space (hash partitioning) attributes
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.selectable replication factoryesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)no infoCan implement custom security layer via applicationsyesfine grained access rights according to SQL-standard

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More resources
Amazon NeptuneFatDBSolrTimescaleDB
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