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

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

Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonBigchainDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIngres  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 ScioreBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWell established RDBMSWidely used in-process key-value store
Primary database modelKey-value storeDocument storeDocument storeRelational DBMSKey-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
Score1.85
Rank#138  Overall
#24  Key-value stores
Score0.79
Rank#212  Overall
#36  Document stores
Score4.47
Rank#76  Overall
#12  Document stores
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Websiteaws.amazon.com/­simpledbwww.bigchaindb.comcloud.google.com/­datastorewww.actian.com/­databases/­ingreswww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationdocs.aws.amazon.com/­simpledbbigchaindb.readthedocs.io/­en/­latestcloud.google.com/­datastore/­docsdocs.actian.com/­ingresdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperAmazonGoogleActian CorporationOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release2007201620081974 infooriginally developed at University Berkely in early 1970s1994
Current release11.2, May 202218.1.40, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoAGPL v3commercialcommercialOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePythonCC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemshostedLinuxhostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeschema-freeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or datenonoyes, 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.nonono infobut tools for importing/exporting data from/to XML-files availableyes infoonly with the Berkeley DB XML edition
Secondary indexesyes infoAll columns are indexed automaticallyyesyesyes
SQL infoSupport of SQLnonoSQL-like query language (GQL)yesyes infoSQL interfaced based on SQLite is available
APIs and other access methodsRESTful HTTP APICLI Client
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
Go
Haskell
Java
JavaScript
Python
Ruby
.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 proceduresnousing Google App Engineyesno
TriggersnoCallbacks using the Google Apps Engineyesyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslynone
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorMulti-source replication using PaxosIngres ReplicatorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownono
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 integritynonoyes infovia ReferenceProperties or Ancestor pathsyesno
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 TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCC
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yesAccess 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 SimpleDBBigchainDBGoogle Cloud DatastoreIngresOracle Berkeley DB
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