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DBMS > Amazon Aurora vs. CrateDB vs. Google Cloud Spanner vs. Sadas Engine

System Properties Comparison Amazon Aurora vs. CrateDB vs. Google Cloud Spanner vs. Sadas Engine

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonCrateDB  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonDistributed Database based on LuceneA 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.SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelRelational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.84
Rank#44  Overall
#28  Relational DBMS
Score0.69
Rank#226  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#11  Vector DBMS
Score2.69
Rank#101  Overall
#51  Relational DBMS
Score0.00
Rank#385  Overall
#159  Relational DBMS
Websiteaws.amazon.com/­rds/­auroracratedb.comcloud.google.com/­spannerwww.sadasengine.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlcratedb.com/­docscloud.google.com/­spanner/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperAmazonCrateGoogleSADAS s.r.l.
Initial release2015201320172006
Current release5.8.1, August 20248.0
License infoCommercial or Open SourcecommercialOpen Sourcecommercialcommercial infofree trial version available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemshostedAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedAIX
Linux
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
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 SQLyesyes, but no triggers and constraints, and PostgreSQL compatibilityyes infoQuery statements complying to ANSI 2011yes
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
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
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresyesuser defined functions (Javascript)nono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationConfigurable replication on table/partition-levelMulti-source replication with 3 replicas for regional instances.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID 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.yesnonoyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlfine grained access rights according to SQL-standardrights management via user accountsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles according to SQL-standard

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More resources
Amazon AuroraCrateDBGoogle Cloud SpannerSadas Engine
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23 July 2024, InfoWorld

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