AppWrite VS Qdrant
Compare AppWrite VS Qdrant and see what are their differences
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AppWrite
Supabase
Firebase
Clerk
PocketBase.io
Convex.dev
Directus
Next.js
Qdrant
Weaviate
Milvus
Vespa.ai
Pinecone
ElasticSearch
Zilliz
Algolia
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.
AppWrite QdrantAppWrite is recommended for developers building applications who require a scalable backend solution without the overhead of managing infrastructure. It is particularly suited for developers who prefer open-source platforms and those who want to avoid vendor lock-in. AppWrite's features make it a good fit for startups, hobby projects, and even educational purposes where full control over the backend is desirable.
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.
I've use it instead of Firebase on a 15$ DigitalOcean droplet and saved around ~$150 a month. Managing my own infra does take some extra time, but definitely worth it. The APIs and SDK are also surprisingly much easier to consume than Firebase. Waiting for the cloud version.
Based on our record, AppWrite should be more popular than Qdrant. It has been mentiond 178 times since March 2021. 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.
Initially, I was using the Supabase free tier, but I was hitting the limits, and my app was becoming stale. Then I switched to Appwrite. Both are totally different; one is SQL, while the latter one is NoSQL. Although use node-appwrite package to skip the manual schema add-ons. - Source: dev.to / 5 months ago
Appwrite is an open-source platform that simplifies backend setup by providing authentication, databases, storage, functions, and hosting all in one place. - Source: dev.to / 8 months ago
I love Appwrite. My first hackathon was actually from Appwrite (using Appwrite) 2 years ago, and I've been using it ever since. - Source: dev.to / 12 months ago
Appwrite | Remote | Platform Engineers, AI, Interns | https://www.appwrite.careers Appwrite (https://appwrite.io) is an open-source backend platform that helps developers build secure web and mobile apps faster. Weโre hiring engineers across multiple teams to improve infrastructure, expand developer tooling, and scale our platform. Open roles: โ Platform Engineer. - Source: Hacker News / about 1 year ago
Appwrite is a backend-as-a-service platform that provides authentication, storage, and database. Appwrite is used for authentication and storage. - Source: dev.to / about 1 year ago
The stack runs on Qdrant for vector storage, Ollama for local embeddings, and optional Neo4j for a knowledge graph that I added later. I also set it up to route different operations to the best LLM for each task. It provides eleven tools for your Claude Code instance to manage long-term memory operations, and your memories data never leaves your machine. - Source: dev.to / 5 months ago
Qdrant: Open-source vector database optimized for hybrid search and easy integration with ML workflows. - Source: dev.to / 7 months ago
Yes, Java SDKs are critical. But you don't need to rebuild entire orchestration engines just to write agents in Java. The ecosystem already has platforms solving the hard problems: memory (Zep, Mem0, LangMem), tools (specialized platforms), vectors (Pinecone, Weaviate, Qdrant), observability (LangSmith, Helicone, Langfuse). Integrate, don't rebuild. - Source: dev.to / 8 months ago
James Allsopp adds, "LangChain or LlamaIndex for managing LLM workflows, especially if you're adding vector search or documents." These tools handle multi-step processes, essential for complex apps. - Source: dev.to / 11 months ago
๐ฆ Qdrant for fast vector search and retrieval. - Source: dev.to / 11 months ago
Supabase - An open source Firebase alternative
Weaviate - Welcome to Weaviate
Firebase - Firebase is a cloud service designed to power real-time, collaborative applications for mobile and web.
Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.
Clerk - Clerk.io, the artificial intelligence for e-commerce that knows your customers interests.
Vespa.ai - Store, search, rank and organize big data