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

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

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonHBase  Xexclude from comparisonSpark SQL  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudWide-column store based on Apache Hadoop and on concepts of BigTableSpark 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 virtualization
Primary database modelGraph DBMS
RDF store
Wide column storeRelational DBMSGraph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score27.97
Rank#26  Overall
#2  Wide column stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Websiteaws.amazon.com/­neptunehbase.apache.orgspark.apache.org/­sqlwww.stardog.com
Technical documentationaws.amazon.com/­neptune/­developer-resourceshbase.apache.org/­book.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.stardog.com
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software FoundationStardog-Union
Initial release2017200820142010
Current release2.3.4, January 20213.5.0 ( 2.13), September 20237.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoApache 2.0commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaJava
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
Linux
macOS
Windows
Data schemeschema-freeschema-free, schema definition possibleyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyes
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 infoImport/export of XML data possible
Secondary indexesnononoyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Java API
RESTful HTTP API
Thrift
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
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
Java
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javanouser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyesnoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, 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.Multi-source replication
Source-replica replication
noneMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyes infoRelationships in graphsnonoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)noACID
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.yesnoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnoAccess rights for users and roles

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More resources
Amazon NeptuneHBaseSpark SQLStardog
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