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DBMS > Apache Impala vs. Milvus vs. Percona Server for MySQL vs. Solr

System Properties Comparison Apache Impala vs. Milvus vs. Percona Server for MySQL vs. Solr

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonMilvus  Xexclude from comparisonPercona Server for MySQL  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA DBMS designed for efficient storage of vector data and vector similarity searchesEnhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSVector DBMSRelational DBMSSearch engine
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score2.78
Rank#103  Overall
#3  Vector DBMS
Score2.10
Rank#119  Overall
#57  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websiteimpala.apache.orgmilvus.iowww.percona.com/­software/­mysql-database/­percona-serversolr.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmlmilvus.io/­docs/­overview.mdwww.percona.com/­downloads/­Percona-Server-LATESTsolr.apache.org/­resources.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaPerconaApache Software Foundation
Initial release2013201920082006
Current release4.1.0, June 20222.3.4, January 20248.0.36-28, 20249.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoGPL version 2Open 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.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC++C++, GoC and C++Java
Server operating systemsLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
LinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringyesyes 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.nonoyesyes
Secondary indexesyesnoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIADO.NET
JDBC
ODBC
Java API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCC++
Go
Java
JavaScript (Node.js)
Python
Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyesJava plugins
Triggersnonoyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
XtraDB Cluster
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDoptimistic 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.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosRole based access control and fine grained access rightsUsers with fine-grained authorization concept infono user groups or rolesyes
More information provided by the system vendor
Apache ImpalaMilvusPercona Server for MySQLSolr
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
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Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
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Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
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Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
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Apache ImpalaMilvusPercona Server for MySQLSolr
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