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DBMS > Amazon SimpleDB vs. Google Cloud Datastore vs. OpenMLDB vs. Oracle Berkeley DB

System Properties Comparison Amazon SimpleDB vs. Google Cloud Datastore vs. OpenMLDB vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonOpenMLDB  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
DescriptionHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn open-source machine learning database that provides a feature platform for training and inferenceWidely used in-process key-value store
Primary database modelKey-value storeDocument storeTime Series DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.88
Rank#133  Overall
#23  Key-value stores
Score4.36
Rank#72  Overall
#12  Document stores
Score0.10
Rank#359  Overall
#36  Time Series DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Websiteaws.amazon.com/­simpledbcloud.google.com/­datastoreopenmldb.aiwww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationdocs.aws.amazon.com/­simpledbcloud.google.com/­datastore/­docsopenmldb.ai/­docs/­zh/­maindocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperAmazonGoogle4 Paradigm Inc.Oracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release2007200820201994
Current release2024-2 February 202418.1.40, May 2020
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java, ScalaC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemshostedhostedLinuxAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeschema-freeschema-freeFixed schemaschema-free
Typing infopredefined data types such as float or datenoyes, 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.nonoyes infoonly with the Berkeley DB XML edition
Secondary indexesyes infoAll columns are indexed automaticallyyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)yesyes infoSQL interfaced based on SQLite is available
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
SQLAlchemy
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Go
Java
Python
Scala
.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
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresnousing Google App Enginenono
TriggersnoCallbacks using the Google Apps Enginenoyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardinghorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using PaxosSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
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 integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
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.noyesyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access 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 SimpleDBGoogle Cloud DatastoreOpenMLDBOracle Berkeley DB
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