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

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

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonGoogle Cloud Datastore  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 ScioreA scale-out RDBMS with evolutionary schema built on Apache HBaseAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWidely used in-process key-value store
Primary database modelKey-value storeRelational DBMSDocument storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.88
Rank#133  Overall
#23  Key-value stores
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Websiteaws.amazon.com/­simpledbphoenix.apache.orgcloud.google.com/­datastorewww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationdocs.aws.amazon.com/­simpledbphoenix.apache.orgcloud.google.com/­datastore/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperAmazonApache Software FoundationGoogleOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release2007201420081994
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201918.1.40, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemshostedLinux
Unix
Windows
hostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeschema-freeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-free
Typing infopredefined data types such as float or datenoyesyes, details hereno
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 SQLnoyesSQL-like query language (GQL)yes infoSQL interfaced based on SQLite is available
APIs and other access methodsRESTful HTTP APIJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.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 proceduresnouser defined functionsusing Google App Engineno
TriggersnonoCallbacks using the Google Apps Engineyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Multi-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoHadoop integrationyes 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 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.
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
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.yesnoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
Amazon SimpleDBApache PhoenixGoogle Cloud DatastoreOracle Berkeley DB
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