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DBMS > Amazon Aurora vs. Google Cloud Datastore vs. InfluxDB vs. MySQL

System Properties Comparison Amazon Aurora vs. Google Cloud Datastore vs. InfluxDB vs. MySQL

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInfluxDB  Xexclude from comparisonMySQL  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDBMS for storing time series, events and metricsWidely used open source RDBMS
Primary database modelRelational DBMSDocument storeTime Series DBMSRelational DBMS infoKey/Value like access via memcached API
Secondary database modelsDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.38
Rank#48  Overall
#29  Relational DBMS
Score5.25
Rank#58  Overall
#9  Document stores
Score19.62
Rank#33  Overall
#1  Time Series DBMS
Score1283.06
Rank#2  Overall
#2  Relational DBMS
Websiteaws.amazon.com/­rds/­auroracloud.google.com/­datastorewww.influxdata.com/­time-series-platform/­influxdbwww.mysql.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­UserGuide/­CHAP_Aurora.htmlcloud.google.com/­datastore/­docsdocs.influxdata.com/­influxdbdev.mysql.com/­doc
DeveloperAmazonGoogleOracle infosince 2010, originally MySQL AB, then Sun
Initial release2015200820131995
Current release1.7.8, August 20198.0.17, July 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMIT-License; commercial enterprise version availableOpen Source infoGPL version 2. Commercial licenses with extended functionallity are available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
  • Google Cloud SQL: A fully-managed database service for the Google Cloud Platform
  • Azure Database for MySQL: A fully managed, scalable MySQL relational database with high availability and security built in at no extra cost
Implementation languageGoC and C++
Server operating systemshostedhostedLinux
OS X infothrough Homebrew
FreeBSD
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details hereNumeric data and Stringsyes
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.yesnonoyes
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesSQL-like query language (GQL)SQL-like query languageyes infowith proprietary extensions
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
JSON over UDP
Proprietary native API
ADO.NET
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
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesusing Google App Enginenoyes infoproprietary syntax
TriggersyesCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infoin enterprise version onlyhorizontal partitioning, sharding with MySQL Cluster or MySQL Fabric
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-slave replicationMulti-Master replication using Paxosselectable replication factor infoin enterprise version onlyMaster-master replication
Master-slave replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infonot for MyISAM storage engine
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoDepending on used storage engineyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple rights management via user accountsUsers with fine-grained authorization concept infono user groups or roles

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More resources
Amazon AuroraGoogle Cloud DatastoreInfluxDBMySQL
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