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DBMS > Amazon Neptune vs. Citus vs. Hazelcast vs. Microsoft Azure Table Storage

System Properties Comparison Amazon Neptune vs. Citus vs. Hazelcast vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonCitus  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA widely adopted in-memory data gridA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelGraph DBMS
RDF store
Relational DBMSKey-value storeWide column store
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Websiteaws.amazon.com/­neptunewww.citusdata.comhazelcast.comazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.citusdata.comhazelcast.org/­imdg/­docs
DeveloperAmazonHazelcastMicrosoft
Initial release2017201020082012
Current release8.1, December 20185.3.6, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoAGPL, commercial license also availableOpen Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJava
Server operating systemshostedLinuxAll OS with a Java VMhosted
Data schemeschema-freeyesschema-freeschema-free
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.noyes infospecific XML type available, but no XML query functionalityyes infothe object must implement a serialization strategyno
Secondary indexesnoyesyesno
SQL infoSupport of SQLnoyes infostandard, with numerous extensionsSQL-like query languageno
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infoEvent Listeners, Executor Servicesno
Triggersnoyesyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infoImplicit feature of the cloud service
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.Source-replica replication infoother methods possible by using 3rd party extensionsyes infoReplicated Mapyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDone or two-phase-commit; repeatable reads; read commitedoptimistic locking
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.noyesno
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-standardRole-based access controlAccess rights based on private key authentication or shared access signatures

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More resources
Amazon NeptuneCitusHazelcastMicrosoft Azure Table Storage
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