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

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

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonKeyDB  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 casesAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsSpark 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
Key-value storeRelational 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
Score0.71
Rank#226  Overall
#33  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitedruid.apache.orgwww.ibm.com/­products/­db2-event-storegithub.com/­Snapchat/­KeyDB
keydb.dev
spark.apache.org/­sql
Technical documentationdruid.apache.org/­docs/­latest/­designwww.ibm.com/­docs/­en/­db2-event-storedocs.keydb.devspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsIBMEQ Alpha Technology Ltd.Apache Software Foundation
Initial release2012201720192014
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 availableOpen Source infoBSD-3Open Source infoApache 2.0
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++Scala
Server operating systemsLinux
OS X
Unix
Linux infoLinux, macOS, Windows for the developer additionLinuxLinux
OS X
Windows
Data schemeyes infoschema-less columns are supportedyesschema-freeyes
Typing infopredefined data types such as float or dateyesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyes
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 indexesyesnoyes infoby using the Redis Search moduleno
SQL infoSupport of SQLSQL for queryingyes infothrough the embedded Spark runtimenoSQL-like DML and DDL statements
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization ProtocoJDBC
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
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesLuano
Triggersnononono
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
Strong eventual consistency with CRDTs
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoOptimistic locking, atomic execution of commands blocks and scriptsno
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 storageyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes
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-standardsimple password-based access control and ACLno

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More resources
Apache DruidIBM Db2 Event StoreKeyDBSpark SQL
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