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DBMS > Firebase Realtime Database vs. Ignite vs. Spark SQL vs. Splice Machine

System Properties Comparison Firebase Realtime Database vs. Ignite vs. Spark SQL vs. Splice Machine

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Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonIgnite  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Spark SQL is a component on top of 'Spark Core' for structured data processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeKey-value store
Relational DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.29
Rank#39  Overall
#6  Document stores
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitefirebase.google.com/­products/­realtime-databaseignite.apache.orgspark.apache.org/­sqlsplicemachine.com
Technical documentationfirebase.google.com/­docs/­databaseapacheignite.readme.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-works
DeveloperGoogle infoacquired by Google 2014Apache Software FoundationApache Software FoundationSplice Machine
Initial release2012201520142014
Current releaseApache Ignite 2.63.5.0 ( 2.13), September 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java, .NetScalaJava
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyesno
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsyes
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesJava
JavaScript
Objective-C
C#
C++
Java
PHP
Python
Ruby
Scala
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored procedureslimited functionality with using 'rules'yes (compute grid and cache interceptors can be used instead)noyes infoJava
TriggersCallbacks are triggered when data changesyes (cache interceptors and events)noyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)Yes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlyes, based on authentication and database rulesSecurity Hooks for custom implementationsnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Firebase Realtime DatabaseIgniteSpark SQLSplice Machine
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