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DBMS > FoundationDB vs. Google BigQuery vs. Postgres-XL

System Properties Comparison FoundationDB vs. Google BigQuery vs. Postgres-XL

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Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonPostgres-XL  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.
DescriptionOrdered key-value store. Core features are complimented by layers.Large scale data warehouse service with append-only tablesBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.27
Rank#151  Overall
#26  Document stores
#28  Key-value stores
#74  Relational DBMS
Score39.63
Rank#24  Overall
#15  Relational DBMS
Score0.55
Rank#232  Overall
#111  Relational DBMS
Websitewww.foundationdb.orgcloud.google.com/­bigquerywww.postgres-xl.org
Technical documentationapple.github.io/­foundationdbcloud.google.com/­bigquery/­docswww.postgres-xl.org/­documentation
DeveloperFoundationDBGoogle
Initial release201320102014 infosince 2012, originally named StormDB
Current release6.2.28, November 202010 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C
Server operating systemsLinux
OS X
Windows
hostedLinux
macOS
Data schemeschema-free infosome layers support schemasyesyes
Typing infopredefined data types such as float or dateno infosome layers support typingyesyes
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 infoXML type, but no XML query functionality
Secondary indexesnonoyes
SQL infoSupport of SQLsupported in specific SQL layer onlyyesyes infodistributed, parallel query execution
APIs and other access methodsRESTful HTTP/JSON APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresin SQL-layer onlyuser defined functions infoin JavaScriptuser defined functions
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable consistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityin SQL-layer onlynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoSince BigQuery is designed for querying dataACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnoAccess privileges (owner, writer, reader) for whole datasets, not for individual tables infoGoogle Cloud Identity & Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
FoundationDBGoogle BigQueryPostgres-XL
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