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DBMS > Amazon Neptune vs. Google Cloud Bigtable vs. RDF4J vs. Sphinx

System Properties Comparison Amazon Neptune vs. Google Cloud Bigtable vs. RDF4J vs. Sphinx

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelGraph DBMS
RDF store
Key-value store
Wide column store
RDF storeSearch 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
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.74
Rank#222  Overall
#9  RDF stores
Score5.95
Rank#55  Overall
#5  Search engines
Websiteaws.amazon.com/­neptunecloud.google.com/­bigtablerdf4j.orgsphinxsearch.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcescloud.google.com/­bigtable/­docsrdf4j.org/­documentationsphinxsearch.com/­docs
DeveloperAmazonGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Sphinx Technologies Inc.
Initial release2017201520042001
Current release3.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemshostedhostedLinux
OS X
Unix
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesnoyesno
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.nono
Secondary indexesnonoyesyes infofull-text index on all search fields
SQL infoSupport of SQLnononoSQL-like query language (SphinxQL)
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Proprietary protocol
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
Java
PHP
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonoyesno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneSharding 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.Internal replication in Colossus, and regional replication between two clusters in different zonesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyes infoRelationships in graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes infoin-memory storage is supported as wellyes 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.no
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
Amazon NeptuneGoogle Cloud BigtableRDF4J infoformerly known as SesameSphinx
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