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

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

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHBase  Xexclude from comparisonMarkLogic  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLHawkular 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
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score27.97
Rank#26  Overall
#2  Wide column stores
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Websitewww.citusdata.comwww.hawkular.orghbase.apache.orgwww.progress.com/­marklogic
Technical documentationdocs.citusdata.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guidehbase.apache.org/­book.htmlwww.progress.com/­marklogic/­documentation
DeveloperCommunity supported by Red HatApache Software Foundation infoApache top-level project, originally developed by PowersetMarkLogic Corp.
Initial release2010201420082001
Current release8.1, December 20182.3.4, January 202111.0, December 2022
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen 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 languageCJavaJavaC++
Server operating systemsLinuxLinux
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.yes infospecific XML type available, but no XML query functionalitynonoyes
Secondary indexesyesnonoyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsnonoyes infoSQL92
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP 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 languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
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 proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noyes infoCoprocessors in Javayes infovia XQuery or JavaScript
Triggersyesyes 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 nodesSource-replica replication infoother methods possible by using 3rd party extensionsselectable 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 systemImmediate ConsistencyEventual 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.nonoyesyes, with Range Indexes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess 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
CitusHawkular MetricsHBaseMarkLogic
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