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DBMS > etcd vs. Firebase Realtime Database vs. Google Cloud Firestore vs. IRONdb vs. Spark SQL

System Properties Comparison etcd vs. Firebase Realtime Database vs. Google Cloud Firestore vs. IRONdb vs. Spark SQL

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonIRONdb  Xexclude from comparisonSpark SQL  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA distributed reliable key-value storeCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.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 modelKey-value storeDocument storeDocument storeTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score14.29
Rank#39  Overall
#6  Document stores
Score7.85
Rank#51  Overall
#8  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
firebase.google.com/­products/­realtime-databasefirebase.google.com/­products/­firestorewww.circonus.com/solutions/time-series-database/spark.apache.org/­sql
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
firebase.google.com/­docs/­databasefirebase.google.com/­docs/­firestoredocs.circonus.com/irondb/category/getting-startedspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogle infoacquired by Google 2014GoogleCirconus LLC.Apache Software Foundation
Initial release2012201720172014
Current release3.4, August 2019V0.10.20, January 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC and C++Scala
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedhostedLinuxLinux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyesyesyes 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.nonononono
Secondary indexesnoyesyesnono
SQL infoSupport of SQLnononoSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statements
APIs and other access methodsgRPC
JSON over HTTP
Android
iOS
JavaScript API
RESTful HTTP API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
HTTP APIJDBC
ODBC
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Java
JavaScript
Objective-C
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.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 proceduresnolimited functionality with using 'rules'yes, Firebase Rules & Cloud Functionsyes, in Luano
Triggersyes, watching key changesCallbacks are triggered when data changesyes, with Cloud Functionsnono
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 nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replicationconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoUsing Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesyesnono
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.nonono
User concepts infoAccess controlnoyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.nono

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More resources
etcdFirebase Realtime DatabaseGoogle Cloud FirestoreIRONdbSpark SQL
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