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DBMS > Apache Druid vs. GridGain vs. IBM Db2 Event Store vs. KeyDB

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

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGridGain  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonKeyDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataGridGain is an in-memory computing platform, built on Apache IgniteDistributed Event Store optimized for Internet of Things use casesAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols
Primary database modelRelational DBMS
Time Series DBMS
Key-value store
Relational DBMS
Event Store
Time Series DBMS
Key-value store
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
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.71
Rank#226  Overall
#33  Key-value stores
Websitedruid.apache.orgwww.gridgain.comwww.ibm.com/­products/­db2-event-storegithub.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationdruid.apache.org/­docs/­latest/­designwww.gridgain.com/­docs/­index.htmlwww.ibm.com/­docs/­en/­db2-event-storedocs.keydb.dev
DeveloperApache Software Foundation and contributorsGridGain Systems, Inc.IBMEQ Alpha Technology Ltd.
Initial release2012200720172019
Current release29.0.1, April 2024GridGain 8.5.12.0
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercial infofree developer edition availableOpen Source infoBSD-3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .NetC and C++C++
Server operating systemsLinux
OS X
Unix
Linux
OS X
Solaris
Windows
Linux infoLinux, macOS, Windows for the developer additionLinux
Data schemeyes infoschema-less columns are supportedyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes
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.noyesnono
Secondary indexesyesyesnoyes infoby using the Redis Search module
SQL infoSupport of SQLSQL for queryingANSI-99 for query and DML statements, subset of DDLyes infothrough the embedded Spark runtimeno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Java
PHP
Python
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
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)yesLua
Triggersnoyes (cache interceptors and events)nono
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 enginesyes (replicated cache)Active-active shard replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoOptimistic locking, atomic execution of commands blocks and scripts
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesYes - 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 logs
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemSecurity Hooks for custom implementationsfine grained access rights according to SQL-standardsimple password-based access control and ACL

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More resources
Apache DruidGridGainIBM Db2 Event StoreKeyDB
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