DingoDB vs VectorDB Comparison in 2025

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

VectorDB

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

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

VectorDB

Launched	2014-05
Pricing Model	Free
Starting Price
Tech used	Gzip,Nginx
Tag	Semantic Search,Vector Database,Data Analysis

DingoDB Rank/Visit

Global Rank
Country
Month Visit

Top 5 Countries

Traffic Sources

VectorDB Rank/Visit

Global Rank	2833766
Country	United States
Month Visit	7523

Top 5 Countries

29.83%

29.54%

18.98%

13.23%

6.99%

United States India Indonesia Canada Japan

Traffic Sources

6.31%

1.13%

0.06%

5.55%

68.78%

18.17%

social paidReferrals mail referrals search direct

Estimated traffic data from Similarweb

What are some alternatives?

When comparing DingoDB and VectorDB, 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.

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.