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DBMS > Apache Druid vs. Ehcache vs. GridDB vs. KeyDB

System Properties Comparison Apache Druid vs. Ehcache vs. GridDB vs. KeyDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonEhcache  Xexclude from comparisonGridDB  Xexclude from comparisonKeyDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA widely adopted Java cache with tiered storage optionsScalable in-memory time series database optimized for IoT and Big DataAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeTime Series DBMSKey-value store
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score4.64
Rank#68  Overall
#8  Key-value stores
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.70
Rank#229  Overall
#32  Key-value stores
Websitedruid.apache.orgwww.ehcache.orggriddb.netgithub.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationdruid.apache.org/­docs/­latest/­designwww.ehcache.org/­documentationdocs.griddb.netdocs.keydb.dev
DeveloperApache Software Foundation and contributorsTerracotta Inc, owned by Software AGToshiba CorporationEQ Alpha Technology Ltd.
Initial release2012200920132019
Current release29.0.1, April 20243.10.0, March 20225.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2; commercial licenses availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also 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 languageJavaJavaC++C++
Server operating systemsLinux
OS X
Unix
All OS with a Java VMLinuxLinux
Data schemeyes infoschema-less columns are supportedschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestamppartial 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.nononono
Secondary indexesyesnoyesyes infoby using the Redis Search module
SQL infoSupport of SQLSQL for queryingnoSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JCacheJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Proprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
JavaC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
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 proceduresnononoLua
Triggersnoyes infoCache Event Listenersyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infoby using Terracotta ServerShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infoby using Terracotta ServerSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Immediate consistency within container, eventual consistency across containersEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes infosupports JTA and can work as an XA resourceACID at container levelOptimistic locking, atomic execution of commands blocks and scripts
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyesyes 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 systemnoAccess rights for users can be defined per databasesimple password-based access control and ACL
More information provided by the system vendor
Apache DruidEhcacheGridDBKeyDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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Apache DruidEhcacheGridDBKeyDB
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