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DBMS > Amazon Neptune vs. Spark SQL vs. Stardog vs. Typesense

System Properties Comparison Amazon Neptune vs. Spark SQL vs. Stardog vs. Typesense

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonSpark SQL  Xexclude from comparisonStardog  Xexclude from comparisonTypesense  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudSpark SQL is a component on top of 'Spark Core' for structured data processingEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationA typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity
Primary database modelGraph DBMS
RDF store
Relational DBMSGraph DBMS
RDF store
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Score0.76
Rank#219  Overall
#14  Search engines
Websiteaws.amazon.com/­neptunespark.apache.org/­sqlwww.stardog.comtypesense.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcesspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.stardog.comtypesense.org/­docs
DeveloperAmazonApache Software FoundationStardog-Union
Initial release2017201420102015
Current release3.5.0 ( 2.13), September 20237.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentsOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaJavaC++
Server operating systemshostedLinux
OS X
Windows
Linux
macOS
Windows
Linux
Data schemeschema-freeyesschema-free and OWL/RDFS-schema supportschema-free infopre-defined schema optional
Typing infopredefined data types such as float or dateyesyesyesyes
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 infoImport/export of XML data possible
Secondary indexesnonoyes infosupports real-time indexing in full-text and geospatialyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsYes, compatible with all major SQL variants through dedicated BI/SQL Serverno
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
RESTful HTTP API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Java
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
.Net infocommunity maintained
Clojure infocommunity maintained
Dart infocommunity maintained
Go infocommunity maintained
Java infocommunity maintained
JavaScript
Perl infocommunity maintained
PHP
Python
Ruby
Rust infocommunity maintained
Swift infocommunity maintained
Server-side scripts infoStored proceduresnonouser defined functions and aggregates, HTTP Server extensions in Javano
Triggersnonoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark Corenone
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 replication in HA-ClusterMulti-source replication using RAFT
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyes inforelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
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.noyesyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noAccess rights for users and roles

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More resources
Amazon NeptuneSpark SQLStardogTypesense
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