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DBMS > Apache Drill vs. Citus vs. Hazelcast vs. Solr

System Properties Comparison Apache Drill vs. Citus vs. Hazelcast vs. Solr

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Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonCitus  Xexclude from comparisonHazelcast  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA widely adopted in-memory data gridA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value storeSearch engine
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#127  Overall
#23  Document stores
#60  Relational DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score42.91
Rank#24  Overall
#3  Search engines
Websitedrill.apache.orgwww.citusdata.comhazelcast.comsolr.apache.org
Technical documentationdrill.apache.org/­docsdocs.citusdata.comhazelcast.org/­imdg/­docssolr.apache.org/­resources.html
DeveloperApache Software FoundationHazelcastApache Software Foundation
Initial release2012201020082006
Current release1.20.3, January 20238.1, December 20185.3.6, November 20239.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL, commercial license also availableOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaJava
Server operating systemsLinux
OS X
Windows
LinuxAll OS with a Java VMAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesschema-freeyes 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.noyes infospecific XML type available, but no XML query functionalityyes infothe object must implement a serialization strategyyes
Secondary indexesnoyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantyes infostandard, with numerous extensionsSQL-like query languageSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JCache
JPA
Memcached protocol
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesC++.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functionsuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infoEvent Listeners, Executor ServicesJava plugins
Triggersnoyesyes infoEventsyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyes infoReplicated Mapyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDone or two-phase-commit; repeatable reads; read commitedoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentDepending on the underlying data sourceyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourcenoyesyes
User concepts infoAccess controlDepending on the underlying data sourcefine grained access rights according to SQL-standardRole-based access controlyes

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