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DBMS > Hive vs. Milvus vs. Quasardb vs. Spark SQL

System Properties Comparison Hive vs. Milvus vs. Quasardb vs. Spark SQL

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonMilvus  Xexclude from comparisonQuasardb  Xexclude from comparisonSpark SQL  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopA DBMS designed for efficient storage of vector data and vector similarity searchesDistributed, high-performance timeseries databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSVector DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score2.78
Rank#103  Overall
#4  Vector DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitehive.apache.orgmilvus.ioquasar.aispark.apache.org/­sql
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homemilvus.io/­docs/­overview.mddoc.quasar.ai/­masterspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoinitially developed by FacebookquasardbApache Software Foundation
Initial release2012201920092014
Current release3.1.3, April 20222.4.4, May 20243.14.1, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache 2.0
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 languageJavaC++, GoC++Scala
Server operating systemsAll OS with a Java VMLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
BSD
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringyes infointeger and binaryyes
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.nonono
Secondary indexesyesnoyes infowith tagsno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Thrift
RESTful HTTP APIHTTP APIJDBC
ODBC
Supported programming languagesC++
Java
PHP
Python
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoconsistent hashingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication with selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoTransient modeno
User concepts infoAccess controlAccess rights for users, groups and rolesRole based access control and fine grained access rightsCryptographically strong user authentication and audit trailno
More information provided by the system vendor
HiveMilvusQuasardbSpark SQL
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
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...
» more

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HiveMilvusQuasardbSpark SQL
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