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

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

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGeode  Xexclude from comparisonHBase  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 processesWide-column store based on Apache Hadoop and on concepts of BigTableData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeWide column 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
Score30.50
Rank#26  Overall
#2  Wide column stores
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitedruid.apache.orggeode.apache.orghbase.apache.orgwww.ibm.com/­products/­netezza
Technical documentationdruid.apache.org/­docs/­latest/­designgeode.apache.org/­docshbase.apache.org/­book.html
DeveloperApache Software Foundation and contributorsOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Apache Software Foundation infoApache top-level project, originally developed by PowersetIBM
Initial release2012200220082000
Current release29.0.1, April 20241.1, February 20172.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoApache version 2commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
Server operating systemsLinux
OS X
Unix
All OS with a Java VM infothe JDK (8 or later) is also requiredLinux
Unix
Windows infousing Cygwin
Linux infoincluded in appliance
Data schemeyes infoschema-less columns are supportedschema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes
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 indexesyesnonoyes
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
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
All JVM based languages
C++
Groovy
Java
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresnouser defined functionsyes infoCoprocessors in Javayes
Triggersnoyes infoCache Event Listenersyesno
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 methodsnonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes, on a single nodeSingle row ACID (across millions of columns)ACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
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 definableAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACUsers with fine-grained authorization concept

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