DBMS > DataFS vs. Graphite vs. Milvus

System Properties Comparison DataFS vs. Graphite vs. Milvus

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

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

Primary database model

Object oriented DBMS

Time Series DBMS

Vector DBMS

Secondary database models

Graph DBMS

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

Score	0.07
Rank	#362	Overall
	#17	Object oriented DBMS

Score	4.75
Rank	#75	Overall
	#5	Time Series DBMS

Score	1.81
Rank	#144	Overall
	#5	Vector DBMS

Website

newdatabase.com

github.com/graphite-project/graphite-web

milvus.io

Technical documentation

dev.mobiland.com/Overview.xsp

graphite.readthedocs.io

milvus.io/docs/overview.md

Developer

Mobiland AG

Chris Davis

Initial release

2018

2006

2019

Current release

1.1.263, October 2022

2.3.4, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

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

Python

C++, Go

Server operating systems

Windows

Linux
Unix

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

Typing

predefined data types such as float or date

yes

Numeric data only

Vector, Numeric and String

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

SQL

Support of SQL

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

HTTP API
Sockets

RESTful HTTP API

Supported programming languages

.Net
C
C#
C++
VB.Net

JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

Triggers

no, except callback-events from server when changes happened

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

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

Windows-Profile

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

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

DB-Engines blog posts

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

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
10 December 2018, Uber

Grafana Labs Announces Mimir Time Series Database
1 April 2022, Datanami

Getting Started with Monitoring using Graphite
23 January 2015, InfoQ.com

How Grafana made observability accessible
12 June 2023, InfoWorld

Grafana 4.0 Brings Major Enhancements to Leading Visualization Tool
30 November 2016, PR Newswire

provided by Google News

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

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

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

Share this page