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DBMS > Apache IoTDB vs. Heroic vs. Hive vs. Ignite vs. Milvus

System Properties Comparison Apache IoTDB vs. Heroic vs. Hive vs. Ignite vs. Milvus

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHeroic  Xexclude from comparisonHive  Xexclude from comparisonIgnite  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 FlinkTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchdata warehouse software for querying and managing large distributed datasets, built on HadoopApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelTime Series DBMSTime Series DBMSRelational DBMSKey-value store
Relational DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Websiteiotdb.apache.orggithub.com/­spotify/­heroichive.apache.orgignite.apache.orgmilvus.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlspotify.github.io/­heroiccwiki.apache.org/­confluence/­display/­Hive/­Homeapacheignite.readme.io/­docsmilvus.io/­docs/­overview.md
DeveloperApache Software FoundationSpotifyApache Software Foundation infoinitially developed by FacebookApache Software Foundation
Initial release20182014201220152019
Current release1.1.0, April 20233.1.3, April 2022Apache Ignite 2.62.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache Version 2Open Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
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 languageJavaJavaJavaC++, Java, .NetC++, Go
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMLinux
OS X
Solaris
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyesVector, 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.nonoyesno
Secondary indexesyesyes infovia Elasticsearchyesyesno
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statementsANSI-99 for query and DML statements, subset of DDLno
APIs and other access methodsJDBC
Native API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
Thrift
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C++
Java
PHP
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesnoyes infouser defined functions and integration of map-reduceyes (compute grid and cache interceptors can be used instead)no
Triggersyesnonoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesselectable replication factoryes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes infoquery execution via MapReduceyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlyesAccess rights for users, groups and rolesSecurity Hooks for custom implementationsRole based access control and fine grained access rights
More information provided by the system vendor
Apache IoTDBHeroicHiveIgniteMilvus
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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