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DBMS > EXASOL vs. Firebase Realtime Database vs. FoundationDB vs. IRONdb vs. Spark SQL

System Properties Comparison EXASOL vs. Firebase Realtime Database vs. FoundationDB vs. IRONdb vs. Spark SQL

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonFoundationDB  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Ordered 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 modelRelational DBMSDocument storeDocument 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
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.exasol.comfirebase.google.com/­products/­realtime-databasegithub.com/­apple/­foundationdbwww.circonus.com/solutions/time-series-database/spark.apache.org/­sql
Technical documentationwww.exasol.com/­resourcesfirebase.google.com/­docs/­databaseapple.github.io/­foundationdbdocs.circonus.com/irondb/category/getting-startedspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperExasolGoogle infoacquired by Google 2014FoundationDBCirconus LLC.Apache Software Foundation
Initial release20002012201320172014
Current release6.2.28, November 2020V0.10.20, January 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C and C++Scala
Server operating systemshostedLinux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeyesschema-freeschema-free infosome layers support schemasschema-freeyes
Typing infopredefined data types such as float or dateyesyesno 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.nononono
Secondary indexesyesyesnonono
SQL infoSupport of SQLyesnosupported in specific SQL layer onlySQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statements
APIs and other access methods.Net
JDBC
ODBC
WebSocket
Android
iOS
JavaScript API
RESTful HTTP API
HTTP APIJDBC
ODBC
Supported programming languagesJava
Lua
Python
R
Java
JavaScript
Objective-C
.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 proceduresuser defined functionslimited functionality with using 'rules'in SQL-layer onlyyes, in Luano
TriggersyesCallbacks are triggered when data changesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic, 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 methodsyes infoHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Linearizable consistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integrityyesnoin SQL-layer onlynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardyes, based on authentication and database rulesnonono

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More resources
EXASOLFirebase Realtime DatabaseFoundationDBIRONdbSpark SQL
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