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DBMS > Hawkular Metrics vs. Microsoft Azure Table Storage vs. Oracle Berkeley DB vs. PouchDB

System Properties Comparison Hawkular Metrics vs. Microsoft Azure Table Storage vs. Oracle Berkeley DB vs. PouchDB

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Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonPouchDB  Xexclude from comparison
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A Wide Column Store for rapid development using massive semi-structured datasetsWidely used in-process key-value storeJavaScript DBMS with an API inspired by CouchDB
Primary database modelTime Series DBMSWide column storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Websitewww.hawkular.orgazure.microsoft.com/­en-us/­services/­storage/­tableswww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlpouchdb.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.oracle.com/­cd/­E17076_05/­html/­index.htmlpouchdb.com/­guides
DeveloperCommunity supported by Red HatMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software Foundation
Initial release2014201219942012
Current release18.1.40, May 20207.1.1, June 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infocommercial license availableOpen Source
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, Java, C++ (depending on the Berkeley DB edition)JavaScript
Server operating systemsLinux
OS X
Windows
hostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeschema-freeschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnono
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.nonoyes infoonly with the Berkeley DB XML editionno
Secondary indexesnonoyesyes infovia views
SQL infoSupport of SQLnonoyes infoSQL interfaced based on SQLite is availableno
APIs and other access methodsHTTP RESTRESTful HTTP APIHTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesGo
Java
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
JavaScript
Server-side scripts infoStored proceduresnononoView functions in JavaScript
Triggersyes infovia Hawkular Alertingnoyes infoonly for the SQL APIyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraSharding infoImplicit feature of the cloud servicenoneSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandrayes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlnoAccess rights based on private key authentication or shared access signaturesnono

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More resources
Hawkular MetricsMicrosoft Azure Table StorageOracle Berkeley DBPouchDB
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