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DBMS > HBase vs. MarkLogic vs. Spark SQL

System Properties Comparison HBase vs. MarkLogic vs. Spark SQL

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Editorial information provided by DB-Engines
NameHBase  Xexclude from comparisonMarkLogic  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionWide-column store based on Apache Hadoop and on concepts of BigTableOperational and transactional Enterprise NoSQL databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelWide column storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitehbase.apache.orgwww.marklogic.comspark.apache.org/­sql
Technical documentationhbase.apache.org/­book.htmldocs.marklogic.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetMarkLogic Corp.Apache Software Foundation
Initial release200820012014
Current release2.3.4, January 202111.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache version 2commercial inforestricted free version is availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Scala
Server operating systemsLinux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-free, schema definition possibleschema-free infoSchema can be enforcedyes
Typing infopredefined data types such as float or dateoptions 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.noyesno
Secondary indexesnoyesno
SQL infoSupport of SQLnoyes infoSQL92SQL-like DML and DDL statements
APIs and other access methodsJava 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
JDBC
ODBC
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infoCoprocessors in Javayes infovia XQuery or JavaScriptno
Triggersyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataSingle row ACID (across millions of columns)ACID infocan act as a resource manager in an XA/JTA transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, with Range Indexesno
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACRole-based access control at the document and subdocument levelsno

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More resources
HBaseMarkLogicSpark SQL
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