DingoDB VS Vector database for Relevance AI

Let’s have a side-by-side comparison of DingoDB vs Vector database for Relevance AI to find out which one is better. This software comparison between DingoDB and Vector database for Relevance AI is based on genuine user reviews. Compare software prices, features, support, ease of use, and user reviews to make the best choice between these, and decide whether DingoDB or Vector database for Relevance AI fits your business.

DingoDB

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A multi-modal database that provides multi-modal strong consistency data storage such as relationships, vectors, and text, and provides multi-modal joint analysis capabilities based on SQL

Vector database for Relevance AI

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Use managed or self-hosted vector databases to give LLMs the ability to work on YOUR data & context.

DingoDB

Launched	2021-09
Pricing Model	Free
Starting Price
Tech used	cdnjs,Three.js,Gzip,Nginx,Ubuntu,Amazon AWS S3
Tag	Vector Database,Data Analysis,Data Integration

Vector database for Relevance AI

Launched	2018-04
Pricing Model	Free Trial
Starting Price
Tech used	Google Analytics,Google Tag Manager,HubSpot Analytics,Webflow,Amazon AWS CloudFront,Cloudflare CDN,JSDelivr,Google Fonts,jQuery,Gzip,HTTP/3,OpenGraph,HSTS
Tag	Data Science,Vector Database,Data Analysis

DingoDB Rank/Visit

Global Rank
Country
Month Visit

Top 5 Countries

Traffic Sources

Vector database for Relevance AI Rank/Visit

Global Rank	65699
Country	United States
Month Visit	619033

Top 5 Countries

15.11%

13.77%

7.34%

5.26%

5.08%

United States India United Kingdom Cambodia Australia

Traffic Sources

2.28%

0.63%

0.09%

5.34%

42.91%

48.75%

social paidReferrals mail referrals search direct

Estimated traffic data from Similarweb

What are some alternatives?

When comparing DingoDB and Vector database for Relevance AI, you can also consider the following products

Seekdb - OceanBase seekdb is an open-source, AI-native search database that unifies relational, vector, text, JSON and GIS in a single engine, enabling hybrid search and in-database AI workflows.

VectorDB - VectorDB is a simple, lightweight, fully local, end-to-end solution for using embeddings-based text retrieval.

ArangoDB - ArangoDB: The unified multi-model database. Consolidate document, graph & search for high-performance apps & next-gen AI with rich context.

Lancedb - LanceDB: Blazing-fast vector search & multimodal data lakehouse for AI. Unify petabyte-scale data to build & train production-ready AI apps.

CrateDB - CrateDB: High-performance distributed SQL for real-time analytics, search, & AI. Unify data & get instant insights from massive datasets.