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DBMS > Cachelot.io vs. Firebase Realtime Database vs. Hawkular Metrics vs. Microsoft Azure Cosmos DB

System Properties Comparison Cachelot.io vs. Firebase Realtime Database vs. Hawkular Metrics vs. Microsoft Azure Cosmos DB

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Editorial information provided by DB-Engines
NameCachelot.io  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparison
DescriptionIn-memory caching systemCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Globally distributed, horizontally scalable, multi-model database service
Primary database modelKey-value storeDocument storeTime Series DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#383  Overall
#60  Key-value stores
Score14.29
Rank#39  Overall
#6  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score29.04
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Websitecachelot.iofirebase.google.com/­products/­realtime-databasewww.hawkular.orgazure.microsoft.com/­services/­cosmos-db
Technical documentationfirebase.google.com/­docs/­databasewww.hawkular.org/­hawkular-metrics/­docs/­user-guidelearn.microsoft.com/­azure/­cosmos-db
DeveloperGoogle infoacquired by Google 2014Community supported by Red HatMicrosoft
Initial release2015201220142014
License infoCommercial or Open SourceOpen Source infoSimplified BSD LicensecommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java
Server operating systemsFreeBSD
Linux
OS X
hostedLinux
OS X
Windows
hosted
Data schemeschema-freeschema-freeschema-freeschema-free
Typing infopredefined data types such as float or datenoyesyesyes infoJSON 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.nonono
Secondary indexesnoyesnoyes infoAll properties auto-indexed by default
SQL infoSupport of SQLnononoSQL-like query language
APIs and other access methodsMemcached protocolAndroid
iOS
JavaScript API
RESTful HTTP API
HTTP RESTDocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
Supported programming languages.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby
Java
JavaScript
Objective-C
Go
Java
Python
Ruby
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
Server-side scripts infoStored proceduresnolimited functionality with using 'rules'noJavaScript
TriggersnoCallbacks are triggered when data changesyes infovia Hawkular AlertingJavaScript
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infobased on CassandraSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factor infobased on Cassandrayes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononowith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoMulti-item ACID transactions with snapshot isolation within a partition
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentnoyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnoyes, based on authentication and database rulesnoAccess rights can be defined down to the item level

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More resources
Cachelot.ioFirebase Realtime DatabaseHawkular MetricsMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB
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