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DBMS > Apache Druid vs. IBM Db2 warehouse vs. Spark SQL vs. Yanza

System Properties Comparison Apache Druid vs. IBM Db2 warehouse vs. Spark SQL vs. Yanza

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataCloud-based data warehousing serviceSpark SQL is a component on top of 'Spark Core' for structured data processingTime Series DBMS for IoT Applications
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score1.30
Rank#164  Overall
#75  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitedruid.apache.orgwww.ibm.com/­products/­db2/­warehousespark.apache.org/­sqlyanza.com
Technical documentationdruid.apache.org/­docs/­latest/­designspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsIBMApache Software FoundationYanza
Initial release2012201420142015
Current release29.0.1, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache 2.0commercial infofree version available
Cloud-based only infoOnly available as a cloud servicenoyesnono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScala
Server operating systemsLinux
OS X
Unix
hostedLinux
OS X
Windows
Windows
Data schemeyes infoschema-less columns are supportedyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.nono infoImport/export of XML data possiblenono
Secondary indexesyesyesnono
SQL infoSupport of SQLSQL for queryingyesSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
OLE DB
JDBC
ODBC
HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Java
Python
R
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresnoPL/SQL, SQL PLnono
Triggersnoyesnoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesnonenone
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 integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
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.noyesno
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-standardnono

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More resources
Apache DruidIBM Db2 warehouse infoformerly named IBM dashDBSpark SQLYanza
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