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DBMS > Apache Druid vs. Databend vs. Solr vs. Sphinx

System Properties Comparison Apache Druid vs. Databend vs. Solr vs. Sphinx

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDatabend  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityA widely used distributed, scalable search engine based on Apache LuceneOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSSearch engineSearch engine
Secondary database modelsSpatial 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
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websitedruid.apache.orggithub.com/­datafuselabs/­databend
www.databend.com
solr.apache.orgsphinxsearch.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.databend.comsolr.apache.org/­resources.htmlsphinxsearch.com/­docs
DeveloperApache Software Foundation and contributorsDatabend LabsApache Software FoundationSphinx Technologies Inc.
Initial release2012202120062001
Current release29.0.1, April 20241.0.59, April 20239.6.0, April 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2.0Open Source infoApache Version 2Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaRustJavaC++
Server operating systemsLinux
OS X
Unix
hosted
Linux
macOS
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingno
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.nonoyes
Secondary indexesyesnoyes infoAll search fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLSQL for queryingyesSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
RESTful HTTP/JSON API
CLI Client
JDBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Go
Java
JavaScript (Node.js)
Python
Rust
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonoJava pluginsno
Triggersnonoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemUsers with fine-grained authorization concept, user rolesyesno

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Apache DruidDatabendSolrSphinx
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