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DBMS > Cassandra vs. Firebase Realtime Database vs. Microsoft Azure Data Explorer vs. Percona Server for MongoDB vs. Yanza

System Properties Comparison Cassandra vs. Firebase Realtime Database vs. Microsoft Azure Data Explorer vs. Percona Server for MongoDB vs. Yanza

Editorial information provided by DB-Engines
NameCassandra  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionWide-column store based on ideas of BigTable and DynamoDB infoOptimized for write accessCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Fully managed big data interactive analytics platformA drop-in replacement for MongoDB Community Edition with enterprise-grade features.Time Series DBMS for IoT Applications
Primary database modelWide column storeDocument storeRelational DBMS infocolumn orientedDocument storeTime Series DBMS
Secondary database modelsVector DBMS infostarting with release V5Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score101.89
Rank#12  Overall
#1  Wide column stores
Score14.29
Rank#39  Overall
#6  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.52
Rank#254  Overall
#39  Document stores
Websitecassandra.apache.orgfirebase.google.com/­products/­realtime-databaseazure.microsoft.com/­services/­data-explorerwww.percona.com/­mongodb/­software/­percona-server-for-mongodbyanza.com
Technical documentationcassandra.apache.org/­doc/­latestfirebase.google.com/­docs/­databasedocs.microsoft.com/­en-us/­azure/­data-explorerdocs.percona.com/­percona-distribution-for-mongodb
DeveloperApache Software Foundation infoApache top level project, originally developped by FacebookGoogle infoacquired by Google 2014MicrosoftPerconaYanza
Initial release20082012201920152015
Current release4.1.3, July 2023cloud service with continuous releases3.4.10-2.10, November 2017
License infoCommercial or Open SourceOpen Source infoApache version 2commercialcommercialOpen Source infoGPL Version 2commercial infofree version available
Cloud-based only infoOnly available as a cloud servicenoyesyesnono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Astra DB: Multi-cloud DBaaS built on Apache Cassandra.
Implementation languageJavaC++
Server operating systemsBSD
Linux
OS X
Windows
hostedhostedLinuxWindows
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesno
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.nonoyesnono
Secondary indexesrestricted infoonly equality queries, not always the best performing solutionyesall fields are automatically indexedyesno
SQL infoSupport of SQLSQL-like SELECT, DML and DDL statements (CQL)noKusto Query Language (KQL), SQL subsetnono
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language, an SQL-like language)
Thrift
Android
iOS
JavaScript API
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
proprietary protocol using JSONHTTP API
Supported programming languagesC#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript infoNode.js
Perl
PHP
Python
Ruby
Scala
Java
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
any language that supports HTTP calls
Server-side scripts infoStored proceduresnolimited functionality with using 'rules'Yes, possible languages: KQL, Python, RJavaScriptno
TriggersyesCallbacks are triggered when data changesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"Sharding infoImplicit feature of the cloud serviceShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infoRepresentation of geographical distribution of servers is possibleyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Eventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Eventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoAtomicity and isolation are supported for single operationsyesnonono
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.nonoyes infovia In-Memory Engine
User concepts infoAccess controlAccess rights for users can be defined per objectyes, based on authentication and database rulesAzure Active Directory AuthenticationAccess rights for users and rolesno
More information provided by the system vendor
CassandraFirebase Realtime DatabaseMicrosoft Azure Data ExplorerPercona Server for MongoDBYanza
Specific characteristicsApache Cassandra is the leading NoSQL, distributed database management system, well...
» more
Competitive advantagesNo single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenariosInternet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customersApple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metricsCassandra is used by 40% of the Fortune 100.
» more
Licensing and pricing modelsApache license  Pricing for commercial distributions provided by DataStax and available...
» more
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