DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache IoTDB vs. EsgynDB vs. Milvus vs. SurrealDB

System Properties Comparison Apache IoTDB vs. EsgynDB vs. Milvus vs. SurrealDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonMilvus  Xexclude from comparisonSurrealDB  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 FlinkEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA DBMS designed for efficient storage of vector data and vector similarity searchesA fully ACID transactional, developer-friendly, multi-model DBMS
Primary database modelTime Series DBMSRelational DBMSVector DBMSDocument store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score0.86
Rank#203  Overall
#34  Document stores
#18  Graph DBMS
Websiteiotdb.apache.orgwww.esgyn.cnmilvus.iosurrealdb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlmilvus.io/­docs/­overview.mdsurrealdb.com/­docs
DeveloperApache Software FoundationEsgynSurrealDB Ltd
Initial release2018201520192022
Current release1.1.0, April 20232.3.4, January 2024v1.5.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2.0Open Source
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++, JavaC++, GoRust
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
macOS
Windows
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesVector, Numeric and Stringyes
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 indexesyesyesno
SQL infoSupport of SQLSQL-like query languageyesnoSQL-like query language
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
ODBC
RESTful HTTP APIGraphQL
RESTful HTTP API
WebSocket
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
All languages supporting JDBC/ODBC/ADO.NetC++
Go
Java
JavaScript (Node.js)
Python
Deno
Go
JavaScript (Node.js)
Rust
Server-side scripts infoStored proceduresyesJava Stored Proceduresno
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding
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 replication between multi datacenters
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 integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
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.yesnoyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardRole based access control and fine grained access rightsyes, based on authentication and database rules
More information provided by the system vendor
Apache IoTDBEsgynDBMilvusSurrealDB
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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache IoTDBEsgynDBMilvusSurrealDB
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

TsFile: A Standard Format for IoT Time Series Data
27 February 2024, The New Stack

AMD EPYC 8324P / 8324PN Siena 32-Core Siena Linux Server Performance Review
10 October 2023, Phoronix

Apache Promotes IoT Database Project
25 September 2020, Datanami

Benchmarking The Performance Impact To AMD Inception Mitigations
15 August 2023, Phoronix

IoTDB Provides Data Management for Industrial Edge IT
15 October 2020, The New Stack

provided by Google News

How NVIDIA GPU Acceleration Supercharged Milvus Vector Database
26 March 2024, The New Stack

AI-Powered Search Engine With Milvus Vector Database on Vultr
31 January 2024, SitePoint

Milvus 2.4 Unveils Game-Changing Features for Enhanced Vector Search
20 March 2024, GlobeNewswire

Zilliz Unveils Game-Changing Features for Vector Search
22 March 2024, Datanami

IBM watsonx.data’s integrated vector database: unify, prepare, and deliver your data for AI
9 April 2024, IBM

provided by Google News

SD Times Open-Source Project of the Week: SurrealDB
10 May 2024, SDTimes.com

Meet Tobie Morgan Hitchcock, CEO & Co-Founder Of SurrealDB
25 April 2024, TechRound

Cloud, privacy and AI: Trends defining the future of data and databases
27 September 2023, Sifted

SurrealDB raises $6M for its database-as-a-service offering
4 January 2023, TechCrunch

Introducing SurrealDB: A Quantum Leap in Database Technology
11 September 2023, TechRound

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Present your product here