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DBMS > Amazon Aurora vs. Apache Spark (SQL) vs. YugabyteDB

System Properties Comparison Amazon Aurora vs. Apache Spark (SQL) vs. YugabyteDB

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Spark (SQL)  Xexclude from comparisonYugabyteDB  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonApache Spark SQL is a component on top of 'Spark Core' for structured data processingHigh-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.48
Rank#45  Overall
#28  Relational DBMS
Score17.39
Rank#32  Overall
#20  Relational DBMS
Score2.45
Rank#107  Overall
#53  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraspark.apache.org/­sqlwww.yugabyte.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperAmazonApache Software FoundationYugabyte Inc.
Initial release201520142017
Current release3.5.0 ( 2.13), September 20232.19, September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC and C++
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Data schemeyesyesdepending on used data model
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.yesnono
Secondary indexesyesnoyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes, PostgreSQL compatible
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
Python
R
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresyesnoyes infosql, plpgsql, C
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningyes, utilizing Spark CoreHash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyStrong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardnoyes

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More resources
Amazon AuroraApache Spark (SQL)YugabyteDB
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