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DBMS > FoundationDB vs. IRONdb vs. Spark SQL

System Properties Comparison FoundationDB vs. IRONdb vs. Spark SQL

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Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonIRONdb  Xexclude from comparisonSpark SQL  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionOrdered key-value store. Core features are complimented by layers.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicitySpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Time Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.50
Rank#166  Overall
#29  Document stores
#27  Key-value stores
#76  Relational DBMS
Score19.56
Rank#34  Overall
#21  Relational DBMS
Websitegithub.com/­apple/­foundationdbwww.circonus.com/solutions/time-series-database/spark.apache.org/­sql
Technical documentationapple.github.io/­foundationdbdocs.circonus.com/irondb/category/getting-startedspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFoundationDBCirconus LLC.Apache Software Foundation
Initial release201320172014
Current release6.2.28, November 2020V0.10.20, January 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C and C++Scala
Server operating systemsLinux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeschema-free infosome layers support schemasschema-freeyes
Typing infopredefined data types such as float or dateno infosome layers support typingyes infotext, numeric, histogramsyes
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 indexesnonono
SQL infoSupport of SQLsupported in specific SQL layer onlySQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statements
APIs and other access methodsHTTP APIJDBC
ODBC
Supported programming languages.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresin SQL-layer onlyyes, in Luano
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable consistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integrityin SQL-layer onlynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
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 controlnonono

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More resources
FoundationDBIRONdbSpark SQL
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