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DBMS > Alibaba Cloud Table Store vs. Apache IoTDB vs. HBase vs. Milvus

System Properties Comparison Alibaba Cloud Table Store vs. Apache IoTDB vs. HBase vs. Milvus

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Editorial information provided by DB-Engines
NameAlibaba Cloud Table Store  Xexclude from comparisonApache IoTDB  Xexclude from comparisonHBase  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionA fully managed Wide Column Store for large quantities of semi-structured data with real-time accessAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkWide-column store based on Apache Hadoop and on concepts of BigTableA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelWide column storeTime Series DBMSWide column storeVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#297  Overall
#11  Wide column stores
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score27.97
Rank#26  Overall
#2  Wide column stores
Score2.78
Rank#103  Overall
#4  Vector DBMS
Websitewww.alibabacloud.com/­product/­table-storeiotdb.apache.orghbase.apache.orgmilvus.io
Technical documentationwww.alibabacloud.com/­help/­en/­tablestoreiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhbase.apache.org/­book.htmlmilvus.io/­docs/­overview.md
DeveloperAlibabaApache Software FoundationApache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release2016201820082019
Current release1.1.0, April 20232.3.4, January 20212.4.4, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache version 2Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
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++, Go
Server operating systemshostedAll OS with a Java VM (>= 1.8)Linux
Unix
Windows infousing Cygwin
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeschema-freeyesschema-free, schema definition possible
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROVector, Numeric and String
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.nononono
Secondary indexesnoyesnono
SQL infoSupport of SQLnoSQL-like query languagenono
APIs and other access methodsHTTP APIJDBC
Native API
Java API
RESTful HTTP API
Thrift
RESTful HTTP API
Supported programming languagesJava
Python
C
C#
C++
Go
Java
Python
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyesyes infoCoprocessors in Javano
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoSingle row ACID (across millions of columns)no
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 based on subaccounts and tokensyesAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACRole based access control and fine grained access rights
More information provided by the system vendor
Alibaba Cloud Table StoreApache IoTDBHBaseMilvus
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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Alibaba Cloud Table StoreApache IoTDBHBaseMilvus
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