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DBMS > Amazon Aurora vs. Google Cloud Datastore vs. Microsoft SQL Server vs. Oracle Berkeley DB

System Properties Comparison Amazon Aurora vs. Google Cloud Datastore vs. Microsoft SQL Server vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMicrosofts relational DBMSWidely used in-process key-value store
Primary database modelRelational DBMSDocument storeRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsDocument storeDocument store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.75
Rank#47  Overall
#28  Relational DBMS
Score5.21
Rank#61  Overall
#11  Document stores
Score1081.91
Rank#3  Overall
#3  Relational DBMS
Score2.91
Rank#90  Overall
#16  Key-value stores
#2  Native XML DBMS
Websiteaws.amazon.com/­rds/­auroracloud.google.com/­datastorewww.microsoft.com/­en-us/­sql-serverwww.oracle.com/­technetwork/­database/­database-technologies/­berkeleydb/­overview/­index.html
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­UserGuide/­CHAP_Aurora.htmlcloud.google.com/­datastore/­docsdocs.microsoft.com/­en-ie/­sql/­sql-server/­sql-server-technical-documentationdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperAmazonGoogleMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release2015200819891994
Current releaseSQL Server 2019, November 201918.1 (Core), June 2018
License infoCommercial or Open Sourcecommercialcommercialcommercial inforestricted free version is availableOpen Source infocommercial license 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 languageC++C, Java, C++ (depending on the Berkeley DB edition)
Server operating systemshostedhostedLinux
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyes, details hereyesno
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.yesnoyesyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like query language (GQL)yesyes infoSQL interfaced based on SQLite is available
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
OLE DB
Tabular Data Stream (TDS)
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
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
Perl
Python
Tcl
Server-side scripts infoStored proceduresyesusing Google App EngineTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javano
TriggersyesCallbacks using the Google Apps Engineyesyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingtables can be distributed across several files (horizontal partitioning); sharding through federationnone
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-slave replicationMulti-Master replication using Paxosyes, but depending on the SQL-Server EditionMaster-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 pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesnoyesyes
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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Amazon AuroraGoogle Cloud DatastoreMicrosoft SQL ServerOracle Berkeley DB
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