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DBMS > Amazon Aurora vs. Apache IoTDB vs. Google Cloud Datastore vs. Google Cloud Spanner

System Properties Comparison Amazon Aurora vs. Apache IoTDB vs. Google Cloud Datastore vs. Google Cloud Spanner

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache IoTDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.
Primary database modelRelational DBMSTime Series DBMSDocument storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.84
Rank#44  Overall
#28  Relational DBMS
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score2.69
Rank#101  Overall
#51  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraiotdb.apache.orgcloud.google.com/­datastorecloud.google.com/­spanner
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcloud.google.com/­datastore/­docscloud.google.com/­spanner/­docs
DeveloperAmazonApache Software FoundationGoogleGoogle
Initial release2015201820082017
Current release1.1.0, April 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedAll OS with a Java VM (>= 1.8)hostedhosted
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like query languageSQL-like query language (GQL)yes infoQuery statements complying to ANSI 2011
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
Native API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
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
C
C#
C++
Go
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesyesusing Google App Engineno
TriggersyesyesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication using PaxosMulti-source replication with 3 replicas for regional instances.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparkyes infousing Google Cloud Dataflowyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate 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 integrityyesnoyes infovia ReferenceProperties or Ancestor pathsyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrity
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoStrict serializable isolation
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Amazon AuroraApache IoTDBGoogle Cloud DatastoreGoogle Cloud Spanner
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