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DBMS > FoundationDB vs. Spark SQL vs. YDB

System Properties Comparison FoundationDB vs. Spark SQL vs. YDB

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Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonYDB  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.Spark SQL is a component on top of 'Spark Core' for structured data processingA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMSDocument store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.07
Rank#188  Overall
#31  Document stores
#28  Key-value stores
#86  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.34
Rank#285  Overall
#43  Document stores
#130  Relational DBMS
Websitegithub.com/­apple/­foundationdbspark.apache.org/­sqlgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationapple.github.io/­foundationdbspark.apache.org/­docs/­latest/­sql-programming-guide.htmlydb.tech/­en/­docs
DeveloperFoundationDBApache Software FoundationYandex
Initial release201320142019
Current release6.2.28, November 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Scala
Server operating systemsLinux
OS X
Windows
Linux
OS X
Windows
Linux
Data schemeschema-free infosome layers support schemasyesFlexible Schema (defined schema, partial schema, schema free)
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.nono
Secondary indexesnonoyes
SQL infoSupport of SQLsupported in specific SQL layer onlySQL-like DML and DDL statementsSQL-like query language (YQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API (DynamoDB compatible)
Supported programming languages.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
Java
Python
R
Scala
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresin SQL-layer onlynono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable consistencyImmediate Consistency
Foreign keys infoReferential integrityin SQL-layer onlynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
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 controlnonoAccess rights defined for Yandex Cloud users

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More resources
FoundationDBSpark SQLYDB
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