EVA DB VS Qdrant
Compare EVA DB VS Qdrant and see what are their differences
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EVA DB
txtai
Zilliz
Weaviate
Milvus
Vespa.ai
Meilisearch
Hive
Qdrant
Milvus
Vespa.ai
Weaviate
TopK.io
Meilisearch
Elastic
pgvecto.rs
EVA is an open-source AI-relational database with first-class support for deep learning models. It aims to support AI-powered database applications that operate on both structured (tables) and unstructured data (videos, text, podcasts, PDFs, etc.) with deep learning models.
Qdrant is a leading open-source high-performance Vector Database written in Rust with extended metadata filtering support and advanced features. It deploys as an API service providing a search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications. Powering vector similarity search solutions of any scale due to a flexible architecture and low-level optimization. Qdrant is trusted and high-rated by Machine Learning and Data Science teams of top-tier companies worldwide.
EVA DB QdrantNo features have been listed yet.
Qdrant's answer:
Advanced Features, Performance, Scalability, Developer Experience, and Resources Saving.
Qdrant's answer:
Highest performance https://qdrant.tech/benchmarks/, scalability and ease of use.
Qdrant's answer:
Qdrant is written completely in Rust. SDKs available for all popular languages Python, Go, Rust, Java, .NET, etc.
Based on our record, Qdrant seems to be a lot more popular than EVA DB. While we know about 57 links to Qdrant, we've tracked only 1 mention of EVA DB. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
EvaDB plugs AI into traditional SQL databases, so as a first step, we’ll need to install a database. For this article, we’ll use SQLite because it's fast enough for our tests and does not require a proper database server running somewhere. You may choose a different database, if you prefer. - Source: dev.to / over 1 year ago
Qdrant — open-source and super developer-friendly. - Source: dev.to / 8 days ago
The only thing left to do then was to build something that could showcase the power of code ingestion within a vector database, and it immediately clicked in my mind: "Why don't I ingest my entire codebase of solved Go exercises from Exercism?" That's how I created Code-RAGent, your friendly coding assistant based on your personal codebases and grounded in web search. It is built on top of GPT-4.1, powered by... - Source: dev.to / 18 days ago
Qdrant is an easy-to-set-up, highly performing and scalable vector database, that offers numerous functionalities (among which hybrid search and metadata filtering). - Source: dev.to / 22 days ago
In cases where a company possesses a strong technological foundation and faces a substantial workload demanding advanced vector search capabilities, its ideal solution lies in adopting a specialized vector database. Prominent options in this domain include Chroma (having raised $20 million), Zilliz (having raised $113 million), Pinecone (having raised $138 million), Qdrant (having raised $9.8 million), Weaviate... - Source: dev.to / 23 days ago
/filters:no_upscale()/news/2025/04/microsoft-dotnet-ai-template-p2/en/resources/1use-aspire-orchestration-1745167526397.png) A notable addition in Preview 2 is the support for .NET Aspire, enhancing the development toolkit with advanced AI capabilities. The Qdrant vector database can be utilized alongside .NET Aspire to create scalable applications. The template continues to utilize the Retrieval Augmented... - Source: dev.to / 25 days ago
txtai - AI-powered search engine
Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.
Zilliz - Data Infrastructure for AI Made Easy
Vespa.ai - Store, search, rank and organize big data
Weaviate - Welcome to Weaviate
TopK.io - TopK is a cloud-native database intended for search use cases. It comes with keyword search, vector search, and metadata filtering built-in. Easy-to-use search engine loved by developers of all skill levels.