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DBMS > Apache Druid vs. PostgreSQL vs. Snowflake vs. Spark SQL

System Properties Comparison Apache Druid vs. PostgreSQL vs. Snowflake vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSnowflake  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLCloud-based data warehousing service for structured and semi-structured dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Relational DBMSRelational DBMS
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
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score130.36
Rank#8  Overall
#5  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitedruid.apache.orgwww.postgresql.orgwww.snowflake.comspark.apache.org/­sql
Technical documentationdruid.apache.org/­docs/­latest/­designwww.postgresql.org/­docsdocs.snowflake.net/­manuals/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsPostgreSQL Global Development Group infowww.postgresql.org/­developerSnowflake Computing Inc.Apache Software Foundation
Initial release20121989 info1989: Postgres, 1996: PostgreSQL20142014
Current release29.0.1, April 202416.3, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoBSDcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCScala
Server operating systemsLinux
OS X
Unix
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
hostedLinux
OS X
Windows
Data schemeyes infoschema-less columns are supportedyesyes infosupport of semi-structured data formats (JSON, XML, Avro)yes
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyes infospecific XML-type available, but no XML query functionality.yesno
Secondary indexesyesyesno
SQL infoSupport of SQLSQL for queryingyes infostandard with numerous extensionsyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
CLI Client
JDBC
ODBC
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functionsno
Triggersnoyesno infosimilar concept for controling cloud resourcesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedpartitioning by range, list and (since PostgreSQL 11) by hashyesyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replication infoother methods possible by using 3rd party extensionsyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
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.nononono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardUsers with fine-grained authorization concept, user roles and pluggable authenticationno

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More resources
Apache DruidPostgreSQLSnowflakeSpark SQL
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