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DBMS > Amazon DocumentDB vs. Firebase Realtime Database vs. Hawkular Metrics vs. TimescaleDB

System Properties Comparison Amazon DocumentDB vs. Firebase Realtime Database vs. Hawkular Metrics vs. TimescaleDB

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceCloud-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.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument storeDocument storeTime Series DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.43
Rank#143  Overall
#23  Document stores
Score18.02
Rank#38  Overall
#5  Document stores
Score0.06
Rank#324  Overall
#29  Time Series DBMS
Score3.72
Rank#89  Overall
#5  Time Series DBMS
Websiteaws.amazon.com/­documentdbfirebase.google.com/­products/­realtime-databasewww.hawkular.orgwww.timescale.com
Technical documentationaws.amazon.com/­documentdb/­resourcesfirebase.google.com/­docs/­databasewww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.timescale.com
DeveloperGoogle infoacquired by Google 2014Community supported by Red HatTimescale
Initial release2019201220142017
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC
Server operating systemshostedhostedLinux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex 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.nononoyes
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnononoyes infofull PostgreSQL SQL syntax
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Android
iOS
JavaScript API
RESTful HTTP API
HTTP RESTADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Java
JavaScript
Objective-C
Go
Java
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnolimited functionality with using 'rules'nouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
TriggersnoCallbacks are triggered when data changesyes infovia Hawkular Alertingyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infobased on Cassandrayes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasselectable replication factor infobased on CassandraSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsyesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nono
User concepts infoAccess controlAccess rights for users and rolesyes, based on authentication and database rulesnofine grained access rights according to SQL-standard
More information provided by the system vendor
Amazon DocumentDBFirebase Realtime DatabaseHawkular MetricsTimescaleDB
Specific characteristicsTimescale is the creator of TimescaleDB , the first open-source relational database...
» more
Competitive advantagesTimescaleDB is purpose-built to scale and handle time-series data workloads and is...
» more
Typical application scenariosDevOps and Infrastructure Monitoring All monitoring data is time-series data. Efficiently...
» more
Key customersTransferWise, Maersk, AppDynamics, Walmart, Comcast, LaunchDarkly, IBM, NOV, Cisco,...
» more
Market metricsWith over 9,000 GitHub stars and growing, 600,000 active databases, and an active...
» more
Licensing and pricing modelsTimescaleDB comes in 3 versions, including fully managed Cloud-hosted solutions*,...
» more

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More resources
Amazon DocumentDBFirebase Realtime DatabaseHawkular MetricsTimescaleDB
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