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DBMS > Amazon Aurora vs. Databend

System Properties Comparison Amazon Aurora vs. Databend

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Our visitors often compare Amazon Aurora and Databend with ClickHouse, Databricks and StarRocks.

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonDatabend  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity
Primary database modelRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.48
Rank#45  Overall
#28  Relational DBMS
Score0.27
Rank#294  Overall
#133  Relational DBMS
Websiteaws.amazon.com/­rds/­auroragithub.com/­datafuselabs/­databend
www.databend.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.databend.com
DeveloperAmazonDatabend Labs
Initial release20152021
Current release1.0.59, April 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRust
Server operating systemshostedhosted
Linux
macOS
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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.yesno
Secondary indexesyesno
SQL infoSupport of SQLyesyes
APIs and other access methodsADO.NET
JDBC
ODBC
CLI Client
JDBC
RESTful HTTP 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
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresyesno
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers with fine-grained authorization concept, user roles

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More resources
Amazon AuroraDatabend
DB-Engines blog posts

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12 December 2019, Paul Andlinger

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7 February 2017, Matthias Gelbmann

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3 August 2015, Matthias Gelbmann

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Recent citations in the news

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

Introducing scaling to 0 capacity with Amazon Aurora Serverless v2
20 November 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

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

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