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

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

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Spark (SQL)  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonApache Spark SQL is a component on top of 'Spark Core' for structured data processingMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
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
Score4.13
Rank#69  Overall
#37  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraspark.apache.org/­sqlwww.singlestore.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.singlestore.com
DeveloperAmazonApache Software FoundationSingleStore Inc.
Initial release201520142013
Current release3.5.0 ( 2.13), September 20238.5, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infofree developer edition available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC++, Go
Server operating systemshostedLinux
OS X
Windows
Linux info64 bit version required
Data schemeyesyesyes
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 infobut no triggers and foreign keys
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
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
Java
Python
R
Scala
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesnoyes
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningyes, utilizing Spark CoreSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneSource-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infocan define user-defined aggregate functions for map-reduce-style calculations
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.
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-standardnoFine grained access control via users, groups and roles

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More resources
Amazon AuroraApache Spark (SQL)SingleStore infoformer name was MemSQL
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17 October 2022,  Akmal Chaudhri, SingleStore (sponsor) 

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9 June 2022,  Akmal Chaudhri, SingleStore (sponsor) 

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14 February 2022,  Akmal Chaudhri, SingleStore (sponsor) 

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Recent citations in the news

Introducing Amazon Aurora DSQL | Amazon Web Services
3 December 2024, AWS Blog

Accelerate your generative AI application development with Amazon Bedrock Knowledge Bases Quick Create and Amazon Aurora Serverless
7 December 2024, AWS Blog

How Firmex used AWS SCT and AWS DMS to move 65,000 on-premises Microsoft SQL Server databases to an Amazon Aurora PostgreSQL cluster | Amazon Web Services
9 December 2024, AWS Blog

Introducing scaling to 0 capacity with Amazon Aurora Serverless v2
20 November 2024, AWS Blog

New Amazon CloudWatch Database Insights: Comprehensive database observability from fleets to instances
1 December 2024, AWS Blog

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12 November 2024, Simplilearn

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20 June 2024, Snowflake

Sparkle: Standardizing Modular ETL at Uber
15 August 2024, Uber

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SingleStore Welcomes Andy Wild as Chief Revenue Officer
3 December 2024, Business Wire

Third time was the charm for SingleStore in the cloud, CEO says
8 July 2024, The Register

SingleStore acquires BryteFlow to boost data ingestion capabilities
3 October 2024, InfoWorld

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