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DBMS > Apache Solr vs. Apache Spark (SQL) vs. ClickHouse

System Properties Comparison Apache Solr vs. Apache Spark (SQL) vs. ClickHouse

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Editorial information provided by DB-Engines
NameApache Solr  Xexclude from comparisonApache Spark (SQL)  Xexclude from comparisonClickHouse  Xexclude from comparison
DescriptionA widely used distributed, scalable search engine based on Apache LuceneApache Spark SQL is a component on top of 'Spark Core' for structured data processingA high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.
Primary database modelSearch engineRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score32.79
Rank#23  Overall
#3  Search engines
Score21.62
Rank#29  Overall
#18  Relational DBMS
Score18.77
Rank#31  Overall
#19  Relational DBMS
Websitesolr.apache.orgspark.apache.org/­sqlclickhouse.com
Technical documentationsolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlclickhouse.com/­docs
DeveloperApache Software FoundationApache Software FoundationClickhouse Inc.
Initial release200620142016
Current release9.6.1, May 20243.5.0 ( 2.13), September 2023v24.6.2.17-stable, July 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC++
Server operating systemsAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
FreeBSD
Linux
macOS
Data schemeyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or dateyes infosupports customizable data types and automatic typingyesyes
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.yesnono
Secondary indexesyes infoAll search fields are automatically indexednoyes
SQL infoSupport of SQLSolr Parallel SQL InterfaceSQL-like DML and DDL statementsClose to ANSI SQL (SQL/JSON + extensions)
APIs and other access methodsJava API
RESTful HTTP/JSON API
JDBC
ODBC
gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol
Supported programming languages.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
C# info3rd party library
C++
Elixir info3rd party library
Go info3rd party library
Java info3rd party library
JavaScript (Node.js) info3rd party library
Kotlin info3rd party library
Nim info3rd party library
Perl info3rd party library
PHP info3rd party library
Python info3rd party library
R info3rd party library
Ruby info3rd party library
Rust
Scala info3rd party library
Server-side scripts infoStored proceduresJava pluginsnoyes
Triggersyes infoUser configurable commands triggered on index changesnono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corekey based and custom
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneAsynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.
MapReduce infoOffers an API for user-defined Map/Reduce methodsspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlyesnoAccess rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

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More resources
Apache SolrApache Spark (SQL)ClickHouse
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