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DBMS > Hypertable vs. Milvus vs. SiteWhere vs. Spark SQL

System Properties Comparison Hypertable vs. Milvus vs. SiteWhere vs. Spark SQL

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonMilvus  Xexclude from comparisonSiteWhere  Xexclude from comparisonSpark SQL  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAn 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 dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelWide column storeVector DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.81
Rank#144  Overall
#5  Vector DBMS
Score0.06
Rank#367  Overall
#36  Time Series DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitemilvus.iogithub.com/­sitewhere/­sitewherespark.apache.org/­sql
Technical documentationmilvus.io/­docs/­overview.mdsitewhere1.sitewhere.io/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHypertable Inc.SiteWhereApache Software Foundation
Initial release2009201920102014
Current release0.9.8.11, March 20162.3.4, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availableOpen Source infoApache Version 2.0Open Source infoCommon Public Attribution License Version 1.0Open 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 languageC++C++, GoJavaScala
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freepredefined schemeyes
Typing infopredefined data types such as float or datenoVector, Numeric and Stringyesyes
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 indexesrestricted infoonly exact value or prefix value scansnonono
SQL infoSupport of SQLnononoSQL-like DML and DDL statements
APIs and other access methodsC++ API
Thrift
RESTful HTTP APIHTTP RESTJDBC
ODBC
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on HBaseyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelselectable replication factor infobased on HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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.yesnono
User concepts infoAccess controlnoRole based access control and fine grained access rightsUsers with fine-grained authorization conceptno
More information provided by the system vendor
HypertableMilvusSiteWhereSpark 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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HypertableMilvusSiteWhereSpark SQL
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