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DBMS > Amazon CloudSearch vs. FoundationDB vs. Google Cloud Bigtable vs. Oracle Berkeley DB

System Properties Comparison Amazon CloudSearch vs. FoundationDB vs. Google Cloud Bigtable vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonFoundationDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudOrdered key-value store. Core features are complimented by layers.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Widely used in-process key-value store
Primary database modelSearch engineDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Key-value store
Wide column store
Key-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#137  Overall
#12  Search engines
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Websiteaws.amazon.com/­cloudsearchgithub.com/­apple/­foundationdbcloud.google.com/­bigtablewww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationdocs.aws.amazon.com/­cloudsearchapple.github.io/­foundationdbcloud.google.com/­bigtable/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperAmazonFoundationDBGoogleOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release2012201320151994
Current release6.2.28, November 202018.1.40, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache 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 languageC++C, Java, C++ (depending on the Berkeley DB edition)
Server operating systemshostedLinux
OS X
Windows
hostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeyesschema-free infosome layers support schemasschema-freeschema-free
Typing infopredefined data types such as float or dateyesno infosome layers support typingnono
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.noyes infoonly with the Berkeley DB XML edition
Secondary indexesyes infoall search fields are automatically indexednonoyes
SQL infoSupport of SQLnosupported in specific SQL layer onlynoyes infoSQL interfaced based on SQLite is available
APIs and other access methodsHTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languages.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
C#
C++
Go
Java
JavaScript (Node.js)
Python
.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 proceduresnoin SQL-layer onlynono
Triggersnononoyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSyesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable consistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynoin SQL-layer onlynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic single-row operationsACID
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.noyes
User concepts infoAccess controlauthentication via encrypted signaturesnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
Amazon CloudSearchFoundationDBGoogle Cloud BigtableOracle Berkeley DB
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