DBMS > HugeGraph vs. Milvus vs. OpenTSDB

System Properties Comparison HugeGraph vs. Milvus vs. OpenTSDB

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Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

A DBMS designed for efficient storage of vector data and vector similarity searches

Scalable Time Series DBMS based on HBase

Primary database model

Graph DBMS

Vector DBMS

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.15
Rank	#339	Overall
	#33	Graph DBMS

Score	1.81
Rank	#144	Overall
	#5	Vector DBMS

Score	1.73
Rank	#147	Overall
	#12	Time Series DBMS

Website

github.com/hugegraph
hugegraph.apache.org

milvus.io

opentsdb.net

Technical documentation

hugegraph.apache.org/docs

milvus.io/docs/overview.md

opentsdb.net/docs/build/html/index.html

Developer

Baidu

currently maintained by Yahoo and other contributors

Initial release

2018

2019

2011

Current release

0.9

2.3.4, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

LGPL

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

Java

C++, Go

Java

Server operating systems

Linux
macOS
Unix

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

numeric data for metrics, strings for tags

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

also supports composite index and range index

SQL

Support of SQL

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

RESTful HTTP API

HTTP API
Telnet API

Supported programming languages

Groovy
Java
Python

C++
Go
Java
JavaScript (Node.js)
Python

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Users, roles and permissions

Role based access control and fine grained access rights

More information provided by the system vendor

Specific characteristics

Milvus is an open-source and cloud-native vector database built for production-ready...
» more

Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
» more

Typical application scenarios

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more

Key customers

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more

Market metrics

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
» more

Licensing and pricing models

Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

show all

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

show all

Recent citations in the news

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
23 April 2024, GBHackers

provided by Google News

What Is Milvus Vector Database?
6 October 2023, The New Stack

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

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

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

Zilliz Cloud boosts vector database performance
31 January 2024, InfoWorld

provided by Google News

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

Brain Monitoring with Kafka, OpenTSDB, and Grafana
5 August 2016, KDnuggets

MapR to help admins peer into dense Hadoop clusters
28 June 2016, SiliconANGLE News

Comparing InfluxDB, TimescaleDB, and QuestDB Timeseries Databases
30 June 2021, Towards Data Science

provided by Google News

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