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DBMS > Amazon Aurora vs. Google Cloud Spanner vs. MonetDB vs. Sphinx

System Properties Comparison Amazon Aurora vs. Google Cloud Spanner vs. MonetDB vs. Sphinx

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonMonetDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonA 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.A relational database management system that stores data in columnsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSRelational DBMSRelational DBMSSearch engine
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.84
Rank#44  Overall
#28  Relational DBMS
Score2.69
Rank#101  Overall
#51  Relational DBMS
Score1.72
Rank#135  Overall
#62  Relational DBMS
Score5.97
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­rds/­auroracloud.google.com/­spannerwww.monetdb.orgsphinxsearch.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlcloud.google.com/­spanner/­docswww.monetdb.org/­Documentationsphinxsearch.com/­docs
DeveloperAmazonGoogleMonetDB BVSphinx Technologies Inc.
Initial release2015201720042001
Current releaseDec2023 (11.49), December 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMozilla Public License 2.0Open Source infoGPL version 2, commercial licence 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.
Implementation languageCC++
Server operating systemshostedhostedFreeBSD
Linux
OS X
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesno
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.yesno
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLyesyes infoQuery statements complying to ANSI 2011yes infoSQL 2003 with some extensionsSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
native C library infoMAPI library (MonetDB application programming interface)
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
Go
Java
JavaScript (Node.js)
Python
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesnoyes, in SQL, C, Rno
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding via remote tablesSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication with 3 replicas for regional instances.none infoSource-replica replication available in experimental statusnone
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
Foreign keys infoReferential integrityyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoStrict serializable isolationACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
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)fine grained access rights according to SQL-standardno

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More resources
Amazon AuroraGoogle Cloud SpannerMonetDBSphinx
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