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DBMS > Amazon Neptune vs. Apache Phoenix vs. EsgynDB vs. Solr vs. TimescaleDB

System Properties Comparison Amazon Neptune vs. Apache Phoenix vs. EsgynDB vs. Solr vs. TimescaleDB

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache Phoenix  Xexclude from comparisonEsgynDB  Xexclude from comparisonSolr  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudA scale-out RDBMS with evolutionary schema built on Apache HBaseEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA widely used distributed, scalable search engine based on Apache LuceneA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSSearch engineTime Series DBMS
Secondary database modelsSpatial DBMSRelational 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
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websiteaws.amazon.com/­neptunephoenix.apache.orgwww.esgyn.cnsolr.apache.orgwww.timescale.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesphoenix.apache.orgsolr.apache.org/­resources.htmldocs.timescale.com
DeveloperAmazonApache Software FoundationEsgynApache Software FoundationTimescale
Initial release20172014201520062017
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20199.6.0, April 20242.13.0, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, JavaJavaC
Server operating systemshostedLinux
Unix
Windows
LinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeschema-freeyes infolate-bound, schema-on-read capabilitiesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typingnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nononoyesyes
Secondary indexesnoyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnoyesyesSolr Parallel SQL Interfaceyes infofull PostgreSQL SQL syntax
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBCADO.NET
JDBC
ODBC
Java API
RESTful HTTP/JSON API
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
Groovy
Java
PHP
Python
Scala
All languages supporting JDBC/ODBC/ADO.Net.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnouser defined functionsJava Stored ProceduresJava pluginsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnononoyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingyes, across time and space (hash partitioning) attributes
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 replication
Source-replica replication
Multi-source replication between multi datacentersyesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoHadoop integrationyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardyesfine grained access rights according to SQL-standard

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Amazon NeptuneApache PhoenixEsgynDBSolrTimescaleDB
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