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DBMS > Amazon Neptune vs. Apache IoTDB vs. Hypertable vs. Postgres-XL

System Properties Comparison Amazon Neptune vs. Apache IoTDB vs. Hypertable vs. Postgres-XL

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache IoTDB  Xexclude from comparisonHypertable  Xexclude from comparisonPostgres-XL  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionFast, reliable graph database built for the cloudAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkAn open source BigTable implementation based on distributed file systems such as HadoopBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelGraph DBMS
RDF store
Time Series DBMSWide column storeRelational DBMS
Secondary database modelsDocument store
Spatial 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
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websiteaws.amazon.com/­neptuneiotdb.apache.orgwww.postgres-xl.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcesiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.postgres-xl.org/­documentation
DeveloperAmazonApache Software FoundationHypertable Inc.
Initial release2017201820092014 infosince 2012, originally named StormDB
Current release1.1.0, April 20230.9.8.11, March 201610 R1, October 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoGNU version 3. Commercial license availableOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C
Server operating systemshostedAll OS with a Java VM (>= 1.8)Linux
OS X
Windows infoan inofficial Windows port is available
Linux
macOS
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.nonoyes infoXML type, but no XML query functionality
Secondary indexesnoyesrestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLnoSQL-like query languagenoyes infodistributed, parallel query execution
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
Native API
C++ API
Thrift
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
C++
Java
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnoyesnouser defined functions
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardinghorizontal partitioning
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.selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factor on file system level
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID infoMVCC
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.yesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yesnofine grained access rights according to SQL-standard

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More resources
Amazon NeptuneApache IoTDBHypertablePostgres-XL
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