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DBMS > Apache Doris vs. Elasticsearch vs. Solr vs. Vitess

System Properties Comparison Apache Doris vs. Elasticsearch vs. Solr vs. Vitess

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonElasticsearch  Xexclude from comparisonSolr  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricA widely used distributed, scalable search engine based on Apache LuceneScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSSearch engineSearch engineRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Spatial DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.60
Rank#247  Overall
#113  Relational DBMS
Score132.83
Rank#7  Overall
#1  Search engines
Score41.02
Rank#24  Overall
#3  Search engines
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitedoris.apache.org
github.com/­apache/­doris
www.elastic.co/­elasticsearchsolr.apache.orgvitess.io
Technical documentationgithub.com/­apache/­doris/­wikiwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlsolr.apache.org/­resources.htmlvitess.io/­docs
DeveloperApache Software Foundation, originally contributed from BaiduElasticApache Software FoundationThe Linux Foundation, PlanetScale
Initial release2017201020062013
Current release1.2.2, February 20238.6, January 20239.6.1, May 202415.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoElastic LicenseOpen Source infoApache Version 2Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaGo
Server operating systemsLinuxAll OS with a Java VMAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Docker
Linux
macOS
Data schemeyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentyes 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 typingyes
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 indexesyesyes infoAll search fields are automatically indexedyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyesSQL-like query languageSolr Parallel SQL Interfaceyes infowith proprietary extensions
APIs and other access methodsJDBC
MySQL client
Java API
RESTful HTTP/JSON API
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesJava.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsyesJava pluginsyes infoproprietary syntax
Triggersnoyes infoby using the 'percolation' featureyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoES-Hadoop Connectorspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allEventual ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynononoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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.noMemcached and Redis integrationyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyesUsers with fine-grained authorization concept infono user groups or roles

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More resources
Apache DorisElasticsearchSolrVitess
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Recent citations in the news

Apache Doris for Log and Time Series Data Analysis in NetEase: Why Not Elasticsearch and InfluxDB?
5 June 2024, hackernoon.com

Workload Isolation in Apache Doris: Optimizing Resource Management and Performance
25 May 2024, hackernoon.com

How to Digest 15 Billion Logs Per Day and Keep Big Queries Within 1 Second
1 September 2023, KDnuggets

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24 June 2022, InfoWorld

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18 May 2021, The Register

They scaled YouTube -- now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

With Vitess 4.0, database vendor matures cloud-native platform
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