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DBMS > Apache Druid vs. IBM Db2 Event Store vs. PlanetScale vs. Spark SQL

System Properties Comparison Apache Druid vs. IBM Db2 Event Store vs. PlanetScale vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonPlanetScale  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDistributed Event Store optimized for Internet of Things use casesScalable, distributed, serverless MySQL database platform built on top of VitessSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMS
Time Series DBMS
Event Store
Time Series DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial 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
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score1.59
Rank#151  Overall
#70  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitedruid.apache.orgwww.ibm.com/­products/­db2-event-storeplanetscale.comspark.apache.org/­sql
Technical documentationdruid.apache.org/­docs/­latest/­designwww.ibm.com/­docs/­en/­db2-event-storeplanetscale.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsIBMPlanetScaleApache Software Foundation
Initial release2012201720202014
Current release29.0.1, April 20242.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infofree developer edition availablecommercialOpen 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 languageJavaC and C++GoScala
Server operating systemsLinux
OS X
Unix
Linux infoLinux, macOS, Windows for the developer additionDocker
Linux
macOS
Linux
OS X
Windows
Data schemeyes infoschema-less columns are supportedyesyesyes
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.nonono
Secondary indexesyesnoyesno
SQL infoSupport of SQLSQL for queryingyes infothrough the embedded Spark runtimeyes infowith proprietary extensionsSQL-like DML and DDL statements
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
MySQL protocol
ODBC
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesyes infoproprietary syntaxno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesActive-active shard replicationMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engineno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID at shard levelno
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyes infotable locks or row locks depending on storage engineyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
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 infono user groups or rolesno

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More resources
Apache DruidIBM Db2 Event StorePlanetScaleSpark SQL
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