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DBMS > Amazon Aurora vs. CockroachDB vs. Drizzle vs. Solr

System Properties Comparison Amazon Aurora vs. CockroachDB vs. Drizzle vs. Solr

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonCockroachDB  Xexclude from comparisonDrizzle  Xexclude from comparisonSolr  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSRelational DBMSRelational DBMSSearch engine
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score6.15
Rank#55  Overall
#33  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websiteaws.amazon.com/­rds/­aurorawww.cockroachlabs.comsolr.apache.org
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlwww.cockroachlabs.com/­docssolr.apache.org/­resources.html
DeveloperAmazonCockroach LabsDrizzle project, originally started by Brian AkerApache Software Foundation
Initial release2015201520082006
Current release23.1.1, May 20237.2.4, September 20129.6.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0, commercial license availableOpen Source infoGNU GPLOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++Java
Server operating systemshostedLinux
macOS
Windows
FreeBSD
Linux
OS X
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesdynamic schemayesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes 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
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesyes, wire compatible with PostgreSQLyes infowith proprietary extensionsSolr Parallel SQL Interface
APIs and other access methodsADO.NET
JDBC
ODBC
JDBCJDBCJava 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
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
C
C++
Java
PHP
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesnonoJava plugins
Triggersyesnono infohooks for callbacks inside the server can be used.yes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using RAFTMulti-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlPluggable authentication mechanisms infoe.g. LDAP, HTTPyes

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More resources
Amazon AuroraCockroachDBDrizzleSolr
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Recent citations in the news

Join the preview of Amazon Aurora Limitless Database | Amazon Web Services
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