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DBMS > Amazon Aurora vs. Citus vs. Google Cloud Bigtable

System Properties Comparison Amazon Aurora vs. Citus vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonCitus  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Secondary database modelsDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Websiteaws.amazon.com/­rds/­aurorawww.citusdata.comcloud.google.com/­bigtable
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.citusdata.comcloud.google.com/­bigtable/­docs
DeveloperAmazonGoogle
Initial release201520102015
Current release8.1, December 2018
License infoCommercial or Open SourcecommercialOpen Source infoAGPL, commercial license also availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC
Server operating systemshostedLinuxhosted
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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.yesyes infospecific XML type available, but no XML query functionalityno
Secondary indexesyesyesno
SQL infoSupport of SQLyesyes infostandard, with numerous extensionsno
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication infoother methods possible by using 3rd party extensionsInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
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-standardfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Amazon AuroraCitusGoogle Cloud Bigtable
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Recent citations in the news

Handle tables without primary keys while creating Amazon Aurora PostgreSQL zero-ETL integrations with Amazon ...
18 April 2024, AWS Blog

Join the preview of Amazon Aurora Limitless Database | Amazon Web Services
27 November 2023, AWS Blog

New – Amazon Aurora Optimized Reads for Aurora PostgreSQL with up to 8x query latency improvement for I/O ...
8 November 2023, AWS Blog

Knowledge Bases for Amazon Bedrock now supports Amazon Aurora PostgreSQL and Cohere embedding models ...
12 February 2024, AWS Blog

Improve the performance of generative AI workloads on Amazon Aurora with Optimized Reads and pgvector | Amazon ...
9 February 2024, AWS Blog

provided by Google News

Ubicloud wants to build an open source alternative to AWS
5 March 2024, TechCrunch

How Citus Health Uses AWS to Provide Secure and Real-Time Virtual Patient Care - AWS Startups
18 August 2023, AWS Blog

Microsoft Benchmarks Distributed PostgreSQL DBs
10 July 2023, Datanami

Distributed PostgreSQL Benchmarks: Azure Cosmos DB, CockroachDB, and YugabyteDB
8 July 2023, InfoQ.com

Microsoft acquires Citus Data, re-affirming its commitment to Open Source and accelerating Azure PostgreSQL ...
24 January 2019, blogs.microsoft.com

provided by Google News

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

What is Google Bigtable? | Definition from TechTarget
1 March 2022, TechTarget

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

provided by Google News



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