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DBMS > Amazon Aurora vs. EsgynDB vs. Greenplum vs. Prometheus vs. Solr

System Properties Comparison Amazon Aurora vs. EsgynDB vs. Greenplum vs. Prometheus vs. Solr

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonEsgynDB  Xexclude from comparisonGreenplum  Xexclude from comparisonPrometheus  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Open-source Time Series DBMS and monitoring systemA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMSSearch engine
Secondary database modelsDocument storeDocument store
Spatial DBMS
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
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websiteaws.amazon.com/­rds/­aurorawww.esgyn.cngreenplum.orgprometheus.iosolr.apache.org
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.greenplum.orgprometheus.io/­docssolr.apache.org/­resources.html
DeveloperAmazonEsgynPivotal Software Inc.Apache Software Foundation
Initial release20152015200520152006
Current release7.0.0, September 20239.6.1, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache Version 2
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++, JavaGoJava
Server operating systemshostedLinuxLinuxLinux
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesNumeric data onlyyes 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.yesnoyes infosince Version 4.2no infoImport of XML data possibleyes
Secondary indexesyesyesyesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesyesyesnoSolr Parallel SQL Interface
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
JDBC
ODBC
JDBC
ODBC
RESTful HTTP/JSON APIJava API
RESTful HTTP/JSON API
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.NetC
Java
Perl
Python
R
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesJava Stored ProceduresyesnoJava plugins
Triggersyesnoyesnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication between multi datacentersSource-replica replicationyes infoby Federationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencynoneEventual Consistency
Foreign keys infoReferential integrityyesyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesnononoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardnoyes

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More resources
Amazon AuroraEsgynDBGreenplumPrometheusSolr
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