DBMS > Milvus vs. Pinecone vs. RDF4J

System Properties Comparison Milvus vs. Pinecone vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

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

A managed, cloud-native vector database

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Vector DBMS

RDF store

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

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

milvus.io

www.pinecone.io

rdf4j.org

Technical documentation

milvus.io/docs/overview.md

docs.pinecone.io/docs/overview

rdf4j.org/documentation

Developer

Pinecone Systems, Inc

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2019

2004

Current release

2.3.4, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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

C++, Go

Java

Server operating systems

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

hosted

Linux
OS X
Unix
Windows

Data scheme

yes

RDF Schemas

Typing

predefined data types such as float or date

Vector, Numeric and String

String, Number, Boolean

yes

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

SQL

Support of SQL

APIs and other access methods

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

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

Python

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

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

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

User concepts

Access control

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

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Vector databases
2 June 2023, Matthias Gelbmann

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Recent citations in the 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.com

provided by Google News

Pinecone Makes Accurate, Fast, Scalable Generative AI Accessible to Organizations Large and Small with Launch of ...
21 May 2024, PR Newswire

Pinecone launches its serverless vector database out of preview
21 May 2024, TechCrunch

Pinecone launches serverless edition of its vector database on AWS
22 May 2024, SiliconANGLE News

Channel Brief: Dell Explains AI Factory, Informatica AI Research, Pinecone Goes Serverless and More
22 May 2024, Channel E2E

How a Decades-Old Technology and a Paper From Meta Created an AI Industry Standard
21 May 2024, The Wall Street Journal

provided by Google News

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27 January 2020, iProgrammer

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