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DBMS > Drizzle vs. Hawkular Metrics vs. HBase vs. Heroic vs. Microsoft Azure Table Storage

System Properties Comparison Drizzle vs. Hawkular Metrics vs. HBase vs. Heroic vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHBase  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Wide-column store based on Apache Hadoop and on concepts of BigTableTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSTime Series DBMSWide column storeTime Series DBMSWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Websitewww.hawkular.orghbase.apache.orggithub.com/­spotify/­heroicazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidehbase.apache.org/­book.htmlspotify.github.io/­heroic
DeveloperDrizzle project, originally started by Brian AkerCommunity supported by Red HatApache Software Foundation infoApache top-level project, originally developed by PowersetSpotifyMicrosoft
Initial release20082014200820142012
Current release7.2.4, September 20122.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache 2.0Open Source infoApache version 2Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaJavaJava
Server operating systemsFreeBSD
Linux
OS X
Linux
OS X
Windows
Linux
Unix
Windows infousing Cygwin
hosted
Data schemeyesschema-freeschema-free, schema definition possibleschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyesyes
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.nononono
Secondary indexesyesnonoyes infovia Elasticsearchno
SQL infoSupport of SQLyes infowith proprietary extensionsnononono
APIs and other access methodsJDBCHTTP RESTJava API
RESTful HTTP API
Thrift
HQL (Heroic Query Language, a JSON-based language)
HTTP API
RESTful HTTP API
Supported programming languagesC
C++
Java
PHP
Go
Java
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnonoyes infoCoprocessors in Javanono
Triggersno infohooks for callbacks inside the server can be used.yes infovia Hawkular Alertingyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingShardingSharding 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 CassandraMulti-source replication
Source-replica replication
yesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoSingle row ACID (across millions of columns)nooptimistic locking
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.noyesnono
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights based on private key authentication or shared access signatures

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More resources
DrizzleHawkular MetricsHBaseHeroicMicrosoft Azure Table Storage
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