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DBMS > Apache IoTDB vs. HEAVY.AI vs. KeyDB vs. Milvus

System Properties Comparison Apache IoTDB vs. HEAVY.AI vs. KeyDB vs. Milvus

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKeyDB  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelTime Series DBMSRelational DBMSKey-value storeVector DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.71
Rank#226  Overall
#33  Key-value stores
Score2.31
Rank#113  Overall
#3  Vector DBMS
Websiteiotdb.apache.orggithub.com/­heavyai/­heavydb
www.heavy.ai
github.com/­Snapchat/­KeyDB
keydb.dev
milvus.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.heavy.aidocs.keydb.devmilvus.io/­docs/­overview.md
DeveloperApache Software FoundationHEAVY.AI, Inc.EQ Alpha Technology Ltd.
Initial release2018201620192019
Current release1.1.0, April 20235.10, January 20222.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; enterprise edition availableOpen Source infoBSD-3Open Source infoApache Version 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++ and CUDAC++C++, Go
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesVector, 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 indexesyesnoyes infoby using the Redis Search moduleno
SQL infoSupport of SQLSQL-like query languageyesnono
APIs and other access methodsJDBC
Native API
JDBC
ODBC
Thrift
Vega
Proprietary protocol infoRESP - REdis Serialization ProtocoRESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
All languages supporting JDBC/ODBC/Thrift
Python
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesnoLuano
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoRound robinShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Bounded 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 datanonoOptimistic locking, atomic execution of commands blocks and scriptsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardsimple password-based access control and ACLRole based access control and fine grained access rights
More information provided by the system vendor
Apache IoTDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KeyDBMilvus
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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More resources
Apache IoTDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KeyDBMilvus
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