DBMS > HugeGraph vs. Microsoft Azure Cosmos DB vs. Milvus vs. OpenTSDB

System Properties Comparison HugeGraph vs. Microsoft Azure Cosmos DB vs. Milvus vs. OpenTSDB

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Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

Globally distributed, horizontally scalable, multi-model database service

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

Document store
Graph DBMS
Key-value store
Wide column store

Vector DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	2.78
Rank	#103	Overall
	#3	Vector DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Website

github.com/hugegraph
hugegraph.apache.org

azure.microsoft.com/services/cosmos-db

milvus.io

opentsdb.net

Technical documentation

hugegraph.apache.org/docs

learn.microsoft.com/azure/cosmos-db

milvus.io/docs/overview.md

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

Developer

Baidu

Microsoft

currently maintained by Yahoo and other contributors

Initial release

2018

2014

2019

2011

Current release

0.9

2.4.4, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

Open Source

LGPL

Cloud-based only

Only available as a cloud service

yes

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

hosted

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

JSON types

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

yes

All properties auto-indexed by default

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

RESTful HTTP API

HTTP API
Telnet API

Supported programming languages

Groovy
Java
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

JavaScript

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

yes

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

Sharding

Implicit feature of the cloud service

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

yes

Implicit feature of the cloud service

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session 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

Multi-item ACID transactions with snapshot isolation within a partition

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

Access rights can be defined down to the item level

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...
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Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
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Typical application scenarios

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
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Key customers

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