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DBMS > Apache Druid vs. GigaSpaces vs. Netezza vs. Solr

System Properties Comparison Apache Druid vs. GigaSpaces vs. Netezza vs. Solr

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGigaSpaces  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsData warehouse and analytics appliance part of IBM PureSystemsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMS
Time Series DBMS
Document store
Object oriented DBMS infoValues are user defined objects
Relational DBMSSearch engine
Secondary database modelsGraph DBMS
Search engine
Spatial 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
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitedruid.apache.orgwww.gigaspaces.comwww.ibm.com/­products/­netezzasolr.apache.org
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.gigaspaces.com/­latest/­landing.htmlsolr.apache.org/­resources.html
DeveloperApache Software Foundation and contributorsGigaspaces TechnologiesIBMApache Software Foundation
Initial release2012200020002006
Current release29.0.1, April 202415.5, September 20209.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2; Commercial licenses availablecommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .NetJava
Server operating systemsLinux
OS X
Unix
Linux
macOS
Solaris
Windows
Linux infoincluded in applianceAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyes infoschema-less columns are supportedschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typing
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.nono infoXML can be used for describing objects metadatayes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL for queryingSQL-99 for query and DML statementsyesSolr Parallel SQL Interface
APIs and other access methodsJDBC
RESTful HTTP/JSON API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
OLE DB
Java API
RESTful HTTP/JSON API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C++
Java
Python
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoyesyesJava plugins
Triggersnoyes, event driven architecturenoyes infoUser configurable commands triggered on index changes
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 replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoMap-Reduce pattern can be built with XAP task executorsyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDoptimistic locking
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 systemRole-based access controlUsers with fine-grained authorization conceptyes

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Apache DruidGigaSpacesNetezza infoAlso called PureData System for Analytics by IBMSolr
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