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DBMS > Amazon Aurora vs. Apache Phoenix vs. LMDB vs. Spark SQL

System Properties Comparison Amazon Aurora vs. Apache Phoenix vs. LMDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Phoenix  Xexclude from comparisonLMDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonA scale-out RDBMS with evolutionary schema built on Apache HBaseA high performant, light-weight, embedded key-value database librarySpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score1.99
Rank#125  Overall
#21  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraphoenix.apache.orgwww.symas.com/­symas-embedded-database-lmdbspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlphoenix.apache.orgwww.lmdb.tech/­docspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonApache Software FoundationSymasApache Software Foundation
Initial release2015201420112014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20190.9.32, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open SourceOpen Source infoApache 2.0
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 languageJavaCScala
Server operating systemshostedLinux
Unix
Windows
Linux
Unix
Windows
Linux
OS X
Windows
Data schemeyesyes infolate-bound, schema-on-read capabilitiesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes
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.yesnonono
Secondary indexesyesyesnono
SQL infoSupport of SQLyesyesnoSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
JDBCJDBC
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
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesuser defined functionsnono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoHadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
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.yesyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynono

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More resources
Amazon AuroraApache PhoenixLMDBSpark SQL
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