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DBMS > Apache Druid vs. Hypertable vs. Milvus vs. SiteWhere

System Properties Comparison Apache Druid vs. Hypertable vs. Milvus vs. SiteWhere

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHypertable  Xexclude from comparisonMilvus  Xexclude from comparisonSiteWhere  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAn open source BigTable implementation based on distributed file systems such as HadoopA DBMS designed for efficient storage of vector data and vector similarity searchesM2M integration platform for persisting/querying time series data
Primary database modelRelational DBMS
Time Series DBMS
Wide column storeVector DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score0.06
Rank#356  Overall
#35  Time Series DBMS
Websitedruid.apache.orgmilvus.iogithub.com/­sitewhere/­sitewhere
Technical documentationdruid.apache.org/­docs/­latest/­designmilvus.io/­docs/­overview.mdsitewhere1.sitewhere.io/­index.html
DeveloperApache Software Foundation and contributorsHypertable Inc.SiteWhere
Initial release2012200920192010
Current release29.0.1, April 20240.9.8.11, March 20162.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoGNU version 3. Commercial license availableOpen Source infoApache Version 2.0Open Source infoCommon Public Attribution License Version 1.0
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++C++, GoJava
Server operating systemsLinux
OS X
Unix
Linux
OS X
Windows infoan inofficial Windows port is available
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Data schemeyes infoschema-less columns are supportedschema-freepredefined scheme
Typing infopredefined data types such as float or dateyesnoVector, 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 indexesyesrestricted infoonly exact value or prefix value scansnono
SQL infoSupport of SQLSQL for queryingnonono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
C++ API
Thrift
RESTful HTTP APIHTTP REST
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C++
Java
Perl
PHP
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factor on file system levelselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 datanononono
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.noyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoRole based access control and fine grained access rightsUsers with fine-grained authorization concept
More information provided by the system vendor
Apache DruidHypertableMilvusSiteWhere
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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Apache DruidHypertableMilvusSiteWhere
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