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DBMS > Amazon Neptune vs. GraphDB vs. RocksDB vs. Sphinx

System Properties Comparison Amazon Neptune vs. GraphDB vs. RocksDB vs. Sphinx

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparisonRocksDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudEnterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.Embeddable persistent key-value store optimized for fast storage (flash and RAM)Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelGraph DBMS
RDF store
Graph DBMS
RDF store
Key-value storeSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score2.76
Rank#99  Overall
#8  Graph DBMS
#4  RDF stores
Score2.84
Rank#97  Overall
#16  Key-value stores
Score5.97
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­neptunewww.ontotext.comrocksdb.orgsphinxsearch.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesgraphdb.ontotext.com/­documentationgithub.com/­facebook/­rocksdb/­wikisphinxsearch.com/­docs
Social network pagesLinkedInTwitterYouTubeGitHubMedium
DeveloperAmazonOntotextFacebook, Inc.Sphinx Technologies Inc.
Initial release2017200020132001
Current release10.4, October 20239.4.0, June 20243.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercial infoSome plugins of GraphDB Workbench are open sourcedOpen Source infoBSDOpen Source infoGPL version 2, commercial licence available
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 languageJavaC++C++
Server operating systemshostedAll OS with a Java VM
Linux
OS X
Windows
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-free and OWL/RDFS-schema support; RDF shapesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnono
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
Secondary indexesnoyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnostored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBCnoSQL-like query language (SphinxQL)
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1
C++ API
Java API
Proprietary protocol
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C
C++
Go
Java
Perl
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnowell-defined plugin interfaces; JavaScript server-side extensibilitynono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnonenonehorizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supported
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 replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)
Foreign keys infoReferential integrityyes infoRelationships in graphsyes infoConstraint checkingnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
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)Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.nono
More information provided by the system vendor
Amazon NeptuneGraphDB infoformer name: OWLIMRocksDBSphinx
Specific characteristicsOntotext GraphDB is a semantic database engine that allows organizations to build...
» more
Competitive advantagesGraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more
Typical application scenariosMetadata enrichment and management, linked data publishing, semantic inferencing...
» more
Key customers​ GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more
Market metricsGraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more
Licensing and pricing modelsGraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more
News

GraphDB in Action: Using Semantics To Push The Envelope Of Software Engineering, Machine Learning, and E-Health Domains
11 September 2024

Accelerating End-to-end Knowledge Graph Solutions with Ontotext’s LinkedLifeData Inventory: The Case of Target Discovery
30 August 2024

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23 August 2024

Considerations to Creating a Graph Center of Excellence: 5 Elements to Ensure Success
22 August 2024

The Power of Knowledge Graphs – A Chat with Perfect Memory and Ontotext
16 August 2024

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More resources
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