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DBMS > Drizzle vs. Hawkular Metrics vs. HBase vs. MarkLogic

System Properties Comparison Drizzle vs. Hawkular Metrics vs. HBase vs. MarkLogic

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHBase  Xexclude from comparisonMarkLogic  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 BigTableOperational and transactional Enterprise NoSQL database
Primary database modelRelational DBMSTime Series DBMSWide column storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.04
Rank#374  Overall
#38  Time Series DBMS
Score31.25
Rank#26  Overall
#2  Wide column stores
Score6.50
Rank#56  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#5  Search engines
Websitewww.hawkular.orghbase.apache.orgwww.marklogic.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidehbase.apache.org/­book.htmldocs.marklogic.com
DeveloperDrizzle project, originally started by Brian AkerCommunity supported by Red HatApache Software Foundation infoApache top-level project, originally developed by PowersetMarkLogic Corp.
Initial release2008201420082001
Current release7.2.4, September 20122.3.4, January 202111.0, December 2022
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache 2.0Open Source infoApache version 2commercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJavaC++
Server operating systemsFreeBSD
Linux
OS X
Linux
OS X
Windows
Linux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
Data schemeyesschema-freeschema-free, schema definition possibleschema-free infoSchema can be enforced
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes
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
Secondary indexesyesnonoyes
SQL infoSupport of SQLyes infowith proprietary extensionsnonoyes infoSQL92
APIs and other access methodsJDBCHTTP RESTJava API
RESTful HTTP API
Thrift
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Supported programming languagesC
C++
Java
PHP
Go
Java
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresnonoyes infoCoprocessors in Javayes infovia XQuery or JavaScript
Triggersno infohooks for callbacks inside the server can be used.yes infovia Hawkular Alertingyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingSharding
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
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoSingle row ACID (across millions of columns)ACID infocan act as a resource manager in an XA/JTA transaction
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.noyesyes, with Range Indexes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACRole-based access control at the document and subdocument levels

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More resources
DrizzleHawkular MetricsHBaseMarkLogic
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