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DBMS > Apache Druid vs. Hive vs. Milvus vs. QuestDB

System Properties Comparison Apache Druid vs. Hive vs. Milvus vs. QuestDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHive  Xexclude from comparisonMilvus  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality datadata warehouse software for querying and managing large distributed datasets, built on HadoopA DBMS designed for efficient storage of vector data and vector similarity searchesA high performance open source SQL database for time series data
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSVector DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.33
Rank#99  Overall
#51  Relational DBMS
#7  Time Series DBMS
Score64.82
Rank#18  Overall
#12  Relational DBMS
Score1.70
Rank#150  Overall
#5  Vector DBMS
Score2.69
Rank#115  Overall
#8  Time Series DBMS
Websitedruid.apache.orghive.apache.orgmilvus.ioquestdb.io
Technical documentationdruid.apache.org/­docs/­latest/­designcwiki.apache.org/­confluence/­display/­Hive/­Homemilvus.io/­docs/­overview.mdquestdb.io/­docs
DeveloperApache Software Foundation and contributorsApache Software Foundation infoinitially developed by FacebookQuestDB Technology Inc
Initial release2012201220192014
Current release29.0.0, February 20243.1.3, April 20222.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2Open Source infoApache Version 2.0Open 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 languageJavaJavaC++, GoJava (Zero-GC), C++, Rust
Server operating systemsLinux
OS X
Unix
All OS with a Java VMLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
macOS
Windows
Data schemeyes infoschema-less columns are supportedyesyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyesyesVector, Numeric and Stringyes
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 indexesyesyesnono
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsnoSQL with time-series extensions
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
RESTful HTTP APIHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C++
Java
PHP
Python
C++
Go
Java
JavaScript (Node.js)
Python
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reducenono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardinghorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factorSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual 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 datanononoACID for single-table writes
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.noyesyes infothrough memory mapped files
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and rolesRole based access control and fine grained access rights
More information provided by the system vendor
Apache DruidHiveMilvusQuestDB
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Relational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
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High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Financial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» 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
Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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