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DBMS > Databend vs. Firebase Realtime Database vs. Splice Machine

System Properties Comparison Databend vs. Firebase Realtime Database vs. Splice Machine

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
firebase.google.com/­products/­realtime-databasesplicemachine.com
Technical documentationdocs.databend.comfirebase.google.com/­docs/­databasesplicemachine.com/­how-it-works
DeveloperDatabend LabsGoogle infoacquired by Google 2014Splice Machine
Initial release202120122014
Current release1.0.59, April 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageRustJava
Server operating systemshosted
Linux
macOS
hostedLinux
OS X
Solaris
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesnoyesyes
SQL infoSupport of SQLyesnoyes
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
Android
iOS
JavaScript API
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
Java
JavaScript
Objective-C
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnolimited functionality with using 'rules'yes infoJava
TriggersnoCallbacks are triggered when data changesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integration
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 Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesyesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
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.yes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesyes, based on authentication and database rulesAccess rights for users, groups and roles according to SQL-standard

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More resources
DatabendFirebase Realtime DatabaseSplice Machine
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