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DBMS > Apache Druid vs. IBM Db2 Event Store vs. Percona Server for MongoDB vs. Solr

System Properties Comparison Apache Druid vs. IBM Db2 Event Store vs. Percona Server for MongoDB vs. Solr

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonSolr  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 casesA drop-in replacement for MongoDB Community Edition with enterprise-grade features.A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMS
Time Series DBMS
Event Store
Time Series DBMS
Document storeSearch engine
Secondary database modelsSpatial 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
Score0.52
Rank#254  Overall
#39  Document stores
Score42.91
Rank#24  Overall
#3  Search engines
Websitedruid.apache.orgwww.ibm.com/­products/­db2-event-storewww.percona.com/­mongodb/­software/­percona-server-for-mongodbsolr.apache.org
Technical documentationdruid.apache.org/­docs/­latest/­designwww.ibm.com/­docs/­en/­db2-event-storedocs.percona.com/­percona-distribution-for-mongodbsolr.apache.org/­resources.html
DeveloperApache Software Foundation and contributorsIBMPerconaApache Software Foundation
Initial release2012201720152006
Current release29.0.1, April 20242.03.4.10-2.10, November 20179.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infofree developer edition availableOpen Source infoGPL Version 2Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C++Java
Server operating systemsLinux
OS X
Unix
Linux infoLinux, macOS, Windows for the developer additionLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyes infoschema-less columns are supportedyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typing
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.nononoyes
Secondary indexesyesnoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL for queryingyes infothrough the embedded Spark runtimenoSolr Parallel SQL Interface
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
proprietary protocol using JSONJava API
RESTful HTTP/JSON 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
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoyesJavaScriptJava plugins
Triggersnononoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesActive-active shard replicationSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyes
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.noyesyes infovia In-Memory Engineyes
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-standardAccess rights for users and rolesyes

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More resources
Apache DruidIBM Db2 Event StorePercona Server for MongoDBSolr
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