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DBMS > Apache IoTDB vs. Hypertable vs. Milvus vs. Sphinx

System Properties Comparison Apache IoTDB vs. Hypertable vs. Milvus vs. Sphinx

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHypertable  Xexclude from comparisonMilvus  Xexclude from comparisonSphinx  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
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 FlinkAn open source BigTable implementation based on distributed file systems such as HadoopA DBMS designed for efficient storage of vector data and vector similarity searchesOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSWide column storeVector DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteiotdb.apache.orgmilvus.iosphinxsearch.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlmilvus.io/­docs/­overview.mdsphinxsearch.com/­docs
DeveloperApache Software FoundationHypertable Inc.Sphinx Technologies Inc.
Initial release2018200920192001
Current release1.1.0, April 20230.9.8.11, March 20162.3.4, January 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU version 3. Commercial license availableOpen Source infoApache Version 2.0Open Source infoGPL version 2, commercial licence available
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++, GoC++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows infoan inofficial Windows port is available
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoVector, Numeric and Stringno
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.nono
Secondary indexesyesrestricted infoonly exact value or prefix value scansnoyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languagenonoSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
Native API
C++ API
Thrift
RESTful HTTP APIProprietary protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C++
Java
Perl
PHP
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesnonono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factor on file system levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate 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 datanononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlyesnoRole based access control and fine grained access rightsno
More information provided by the system vendor
Apache IoTDBHypertableMilvusSphinx
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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