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DBMS > Apache Druid vs. Geode vs. KeyDB vs. Netezza

System Properties Comparison Apache Druid vs. Geode vs. KeyDB vs. Netezza

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGeode  Xexclude from comparisonKeyDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeKey-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
Score1.92
Rank#131  Overall
#23  Key-value stores
Score0.71
Rank#226  Overall
#33  Key-value stores
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitedruid.apache.orggeode.apache.orggithub.com/­Snapchat/­KeyDB
keydb.dev
www.ibm.com/­products/­netezza
Technical documentationdruid.apache.org/­docs/­latest/­designgeode.apache.org/­docsdocs.keydb.dev
DeveloperApache Software Foundation and contributorsOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.EQ Alpha Technology Ltd.IBM
Initial release2012200220192000
Current release29.0.1, April 20241.1, February 2017
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoBSD-3commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++
Server operating systemsLinux
OS X
Unix
All OS with a Java VM infothe JDK (8 or later) is also requiredLinuxLinux infoincluded in appliance
Data schemeyes infoschema-less columns are supportedschema-freeschema-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.nonono
Secondary indexesyesnoyes infoby using the Redis Search moduleyes
SQL infoSupport of SQLSQL for queryingSQL-like query language (OQL)noyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Java Client API
Memcached protocol
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization ProtocoJDBC
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
All JVM based languages
C++
Groovy
Java
Scala
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
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresnouser defined functionsLuayes
Triggersnoyes infoCache Event Listenersnono
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 enginesMulti-source replicationMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
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 datanoyes, on a single nodeOptimistic locking, atomic execution of commands blocks and scriptsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes 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.noyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights per client and object definablesimple password-based access control and ACLUsers with fine-grained authorization concept

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More resources
Apache DruidGeodeKeyDBNetezza infoAlso called PureData System for Analytics by IBM
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