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DBMS > Apache Druid vs. MarkLogic vs. PostgreSQL

System Properties Comparison Apache Druid vs. MarkLogic vs. PostgreSQL

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonMarkLogic  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataOperational and transactional Enterprise NoSQL databaseWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelRelational DBMS
Time Series DBMS
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.70
Rank#98  Overall
#50  Relational DBMS
#7  Time Series DBMS
Score4.28
Rank#67  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#8  Search engines
Score654.34
Rank#4  Overall
#4  Relational DBMS
Websitedruid.apache.orgwww.progress.com/­marklogicwww.postgresql.org
Technical documentationdruid.apache.org/­docs/­latest/­designwww.progress.com/­marklogic/­documentationwww.postgresql.org/­docs
DeveloperApache Software Foundation and contributorsMarkLogic Corp.PostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release201220011989 info1989: Postgres, 1996: PostgreSQL
Current release30.0.0, June 202411.0, December 202216.4, August 2024
License infoCommercial or Open SourceOpen Source infoApache license v2commercial inforestricted free version is availableOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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PostgreSQL Flex @ STACKIT offers managed PostgreSQL Instances with adjustable CPU, RAM, storage amount and speed and several extensions available, in enterprise grade to perfectly match all application requirements. All 100% GDPR-compliant.
Implementation languageJavaC++C
Server operating systemsLinux
OS X
Unix
Linux
OS X
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyes infoschema-less columns are supportedschema-free infoSchema can be enforcedyes
Typing infopredefined data types such as float or dateyesyesyes
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.noyesyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL for queryingyes infoSQL92yes infostandard with numerous extensions
APIs and other access methodsJDBC
RESTful HTTP/JSON API
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
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnoyes infovia XQuery or JavaScriptuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingpartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesSource-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infocan act as a resource manager in an XA/JTA transactionACID
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.noyes, with Range Indexesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemRole-based access control at the document and subdocument levelsfine grained access rights according to SQL-standard

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More resources
Apache DruidMarkLogicPostgreSQL
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