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DBMS > Apache Doris vs. Apache Druid vs. EsgynDB vs. IBM Db2 Event Store

System Properties Comparison Apache Doris vs. Apache Druid vs. EsgynDB vs. IBM Db2 Event Store

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonApache Druid  Xexclude from comparisonEsgynDB  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparison
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionDistributed Event Store optimized for Internet of Things use cases
Primary database modelRelational DBMSRelational DBMS
Time Series DBMS
Relational DBMSEvent Store
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.60
Rank#247  Overall
#113  Relational DBMS
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Websitedoris.apache.org
github.com/­apache/­doris
druid.apache.orgwww.esgyn.cnwww.ibm.com/­products/­db2-event-store
Technical documentationgithub.com/­apache/­doris/­wikidruid.apache.org/­docs/­latest/­designwww.ibm.com/­docs/­en/­db2-event-store
DeveloperApache Software Foundation, originally contributed from BaiduApache Software Foundation and contributorsEsgynIBM
Initial release2017201220152017
Current release1.2.2, February 202329.0.1, April 20242.0
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache license v2commercialcommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++, JavaC and C++
Server operating systemsLinuxLinux
OS X
Unix
LinuxLinux infoLinux, macOS, Windows for the developer addition
Data schemeyesyes infoschema-less columns are supportedyesyes
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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesSQL for queryingyesyes infothrough the embedded Spark runtime
APIs and other access methodsJDBC
MySQL client
JDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Supported programming languagesJavaClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBC/ADO.NetC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Server-side scripts infoStored proceduresuser defined functionsnoJava Stored Proceduresyes
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infomanual/auto, time-basedShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes, via HDFS, S3 or other storage enginesMulti-source replication between multi datacentersActive-active shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesNo - written data is immutable
Durability infoSupport for making data persistentyesyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache DorisApache DruidEsgynDBIBM Db2 Event Store
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