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DBMS > Amazon Neptune vs. FeatureBase vs. HEAVY.AI vs. Stardog

System Properties Comparison Amazon Neptune vs. FeatureBase vs. HEAVY.AI vs. Stardog

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonFeatureBase  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSGraph DBMS
RDF store
Secondary database modelsSpatial 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
Score0.22
Rank#309  Overall
#139  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websiteaws.amazon.com/­neptunewww.featurebase.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.stardog.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.featurebase.comdocs.heavy.aidocs.stardog.com
DeveloperAmazonMolecula and Pilosa Open Source ContributorsHEAVY.AI, Inc.Stardog-Union
Initial release2017201720162010
Current release2022, May 20225.10, January 20227.3.0, May 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; enterprise edition availablecommercial 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++ and CUDAJava
Server operating systemshostedLinux
macOS
LinuxLinux
macOS
Windows
Data schemeschema-freeyesyesschema-free and OWL/RDFS-schema support
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.nononono infoImport/export of XML data possible
Secondary indexesnononoyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnoSQL queriesyesYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
gRPC
JDBC
Kafka Connector
ODBC
JDBC
ODBC
Thrift
Vega
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
Java
Python
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnonouser defined functions and aggregates, HTTP Server extensions in Java
Triggersnononoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoRound robinnone
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.yesMulti-source replicationMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyes infoRelationships in graphsyesnoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyes, using Linux fsyncyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardAccess rights for users and roles

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More resources
Amazon NeptuneFeatureBaseHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Stardog
Recent citations in the news

Amazon Neptune Analytics is now available in the AWS Europe (London) Region
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Amazon Neptune Analytics is now generally available
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Find and link similar entities in a knowledge graph using Amazon Neptune, Part 2: Vector similarity search | Amazon ...
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Analyze large amounts of graph data to get insights and find trends with Amazon Neptune Analytics | Amazon Web ...
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