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DBMS > Amazon Neptune vs. Hypertable vs. Postgres-XL vs. Solr

System Properties Comparison Amazon Neptune vs. Hypertable vs. Postgres-XL vs. Solr

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonHypertable  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSolr  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 open source BigTable implementation based on distributed file systems such as HadoopBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelGraph DBMS
RDF store
Wide column storeRelational DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websiteaws.amazon.com/­neptunewww.postgres-xl.orgsolr.apache.org
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.postgres-xl.org/­documentationsolr.apache.org/­resources.html
DeveloperAmazonHypertable Inc.Apache Software Foundation
Initial release201720092014 infosince 2012, originally named StormDB2006
Current release0.9.8.11, March 201610 R1, October 20189.6.1, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoGNU version 3. Commercial license availableOpen Source infoMozilla public licenseOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CJava
Server operating systemshostedLinux
OS X
Windows infoan inofficial Windows port is available
Linux
macOS
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesnoyesyes infosupports customizable data types and automatic typing
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 infoXML type, but no XML query functionalityyes
Secondary indexesnorestricted infoonly exact value or prefix value scansyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnonoyes infodistributed, parallel query executionSolr Parallel SQL Interface
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
C++ API
Thrift
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RESTful HTTP/JSON API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C++
Java
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnonouser defined functionsJava plugins
Triggersnonoyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioningSharding
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 factor on file system levelyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoMVCCoptimistic 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.noyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)nofine grained access rights according to SQL-standardyes

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More resources
Amazon NeptuneHypertablePostgres-XLSolr
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