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DBMS > Amazon Aurora vs. EsgynDB vs. Solr vs. Vitess vs. Yaacomo

System Properties Comparison Amazon Aurora vs. EsgynDB vs. Solr vs. Vitess vs. Yaacomo

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonEsgynDB  Xexclude from comparisonSolr  Xexclude from comparisonVitess  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA widely used distributed, scalable search engine based on Apache LuceneScalable, distributed, cloud-native DBMS, extending MySQLOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSSearch engineRelational DBMSRelational DBMS
Secondary database modelsDocument storeSpatial DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorawww.esgyn.cnsolr.apache.orgvitess.ioyaacomo.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlsolr.apache.org/­resources.htmlvitess.io/­docs
DeveloperAmazonEsgynApache Software FoundationThe Linux Foundation, PlanetScaleQ2WEB GmbH
Initial release20152015200620132009
Current release9.6.1, May 202415.0.2, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infoApache Version 2.0, commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaJavaGo
Server operating systemshostedLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Docker
Linux
macOS
Android
Linux
Windows
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyesyes
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.yesnoyesno
Secondary indexesyesyesyes infoAll search fields are automatically indexedyesyes
SQL infoSupport of SQLyesyesSolr Parallel SQL Interfaceyes infowith proprietary extensionsyes
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
JDBC
ODBC
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
MySQL protocol
ODBC
JDBC
ODBC
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
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
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesJava Stored ProceduresJava pluginsyes infoproprietary syntax
Triggersyesnoyes infoUser configurable commands triggered on index changesyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication between multi datacentersyesMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Immediate Consistency
Foreign keys infoReferential integrityyesyesnoyes infonot for MyISAM storage engineyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic lockingACID at shard levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engineyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardyesUsers with fine-grained authorization concept infono user groups or rolesfine grained access rights according to SQL-standard

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More resources
Amazon AuroraEsgynDBSolrVitessYaacomo
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