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DBMS > Amazon Aurora vs. Google BigQuery vs. Google Cloud Bigtable vs. Ingres vs. TDSQL for MySQL

System Properties Comparison Amazon Aurora vs. Google BigQuery vs. Google Cloud Bigtable vs. Ingres vs. TDSQL for MySQL

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonIngres  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonLarge scale data warehouse service with append-only tablesGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Well established RDBMSA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Relational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score0.85
Rank#205  Overall
#95  Relational DBMS
Websiteaws.amazon.com/­rds/­auroracloud.google.com/­bigquerycloud.google.com/­bigtablewww.actian.com/­databases/­ingreswww.tencentcloud.com/­products/­dcdb
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlcloud.google.com/­bigquery/­docscloud.google.com/­bigtable/­docsdocs.actian.com/­ingreswww.tencentcloud.com/­document/­product/­1042
DeveloperAmazonGoogleGoogleActian CorporationTencent
Initial release2015201020151974 infooriginally developed at University Berkely in early 1970s2013
Current release11.2, May 2022
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC
Server operating systemshostedhostedhostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hosted
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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 infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesyesnonoyesyes
SQL infoSupport of SQLyesyesnoyesyes
APIs and other access methodsADO.NET
JDBC
ODBC
RESTful HTTP/JSON APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
JDBC
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
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesuser defined functions infoin JavaScriptnoyesyes
Triggersyesnonoyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnoneShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslyAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationInternal replication in Colossus, and regional replication between two clusters in different zonesIngres ReplicatorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnono
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)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoSince BigQuery is designed for querying dataAtomic single-row operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCCyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnononono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardUsers with fine-grained authorization concept

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More resources
Amazon AuroraGoogle BigQueryGoogle Cloud BigtableIngresTDSQL for MySQL
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