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DBMS > Apache Druid vs. IBM Db2 Event Store vs. MySQL

System Properties Comparison Apache Druid vs. IBM Db2 Event Store vs. MySQL

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMySQL  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 casesWidely used open source RDBMS
Primary database modelRelational DBMS
Time Series DBMS
Event Store
Time Series DBMS
Relational DBMS infoKey/Value like access via memcached API
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.94
Rank#104  Overall
#54  Relational DBMS
#6  Time Series DBMS
Score0.47
Rank#244  Overall
#2  Event Stores
#19  Time Series DBMS
Score1189.21
Rank#2  Overall
#2  Relational DBMS
Websitedruid.apache.orgwww.ibm.com/­products/­db2-event-storewww.mysql.com
Technical documentationdruid.apache.org/­docs/­latest/­designwww.ibm.com/­support/­knowledgecenter/­en/­SSGNPV_2.0.0/­welcome.htmldev.mysql.com/­doc
DeveloperApache Software Foundation and contributorsIBMOracle infosince 2010, originally MySQL AB, then Sun
Initial release201220171995
Current release0.22.1, December 20212.08.0.29, April 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infofree developer edition availableOpen Source infoGPL version 2. Commercial licenses with extended functionallity are available
Cloud-based only infoOnly available as a cloud servicenonono
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Implementation languageJavaC and C++C and C++
Server operating systemsLinux
OS X
Unix
Linux infoLinux, macOS, Windows for the developer additionFreeBSD
Linux
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedyesyes
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.nonoyes
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL for queryingyes infothrough the embedded Spark runtimeyes infowith proprietary extensions
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Proprietary native API
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
Server-side scripts infoStored proceduresnoyesyes infoproprietary syntax
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardinghorizontal partitioning, sharding with MySQL Cluster or MySQL Fabric
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
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infonot for MyISAM storage engine
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
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 roles

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