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

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

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache IoTDB  Xexclude from comparisonCubrid  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 FlinkCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPA 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 DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.20
Rank#169  Overall
#78  Relational DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraiotdb.apache.orgcubrid.com (korean)
cubrid.org (english)
cloud.google.com/­spanner
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcubrid.org/­manualscloud.google.com/­spanner/­docs
DeveloperAmazonApache Software FoundationCUBRID Corporation, CUBRID FoundationGoogle
Initial release2015201820082017
Current release1.1.0, April 202311.0, January 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++, Java
Server operating systemshostedAll OS with a Java VM (>= 1.8)Linux
Windows
hosted
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 languageyesyes infoQuery statements complying to ANSI 2011
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
Native API
ADO.NET
JDBC
ODBC
OLE DB
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
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesyesJava Stored Proceduresno
Triggersyesyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneSharding
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 replicasSource-replica replicationMulti-source replication with 3 replicas for regional instances.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparknoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyes 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 dataACIDnoACIDACID 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-standardyesfine 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 AuroraApache IoTDBCubridGoogle Cloud Spanner
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