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DBMS > CouchDB vs. Firebase Realtime Database vs. Google BigQuery vs. Hawkular Metrics vs. Microsoft Azure Data Explorer

System Properties Comparison CouchDB vs. Firebase Realtime Database vs. Google BigQuery vs. Hawkular Metrics vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Large scale data warehouse service with append-only tablesHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Fully managed big data interactive analytics platform
Primary database modelDocument storeDocument storeRelational DBMSTime Series DBMSRelational DBMS infocolumn oriented
Secondary database modelsSpatial DBMS infousing the Geocouch extensionDocument 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
Score8.30
Rank#47  Overall
#7  Document stores
Score13.64
Rank#39  Overall
#6  Document stores
Score58.10
Rank#19  Overall
#13  Relational DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitecouchdb.apache.orgfirebase.google.com/­products/­realtime-databasecloud.google.com/­bigquerywww.hawkular.orgazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.couchdb.org/­en/­stablefirebase.google.com/­docs/­databasecloud.google.com/­bigquery/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerGoogle infoacquired by Google 2014GoogleCommunity supported by Red HatMicrosoft
Initial release20052012201020142019
Current release3.3.3, December 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache version 2commercialcommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageErlangJava
Server operating systemsAndroid
BSD
Linux
OS X
Solaris
Windows
hostedhostedLinux
OS X
Windows
hosted
Data schemeschema-freeschema-freeyesschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or datenoyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.nonononoyes
Secondary indexesyes infovia viewsyesnonoall fields are automatically indexed
SQL infoSupport of SQLnonoyesnoKusto Query Language (KQL), SQL subset
APIs and other access methodsRESTful HTTP/JSON APIAndroid
iOS
JavaScript API
RESTful HTTP API
RESTful HTTP/JSON APIHTTP RESTMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
Java
JavaScript
Objective-C
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
Go
Java
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresView functions in JavaScriptlimited functionality with using 'rules'user defined functions infoin JavaScriptnoYes, possible languages: KQL, Python, R
TriggersyesCallbacks are triggered when data changesnoyes infovia Hawkular Alertingyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infoimproved architecture with release 2.0noneSharding infobased on CassandraSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factor infobased on Cassandrayes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a single document possibleyesno infoSince BigQuery is designed for querying datanono
Concurrency infoSupport for concurrent manipulation of datayes infostrategy: optimistic lockingyesyesyesyes
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.nononono
User concepts infoAccess controlAccess rights for users can be defined per databaseyes, based on authentication and database rulesAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)noAzure Active Directory Authentication

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More resources
CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Firebase Realtime DatabaseGoogle BigQueryHawkular MetricsMicrosoft Azure Data Explorer
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