canopy
dgraph
canopy | dgraph | |
---|---|---|
14 | 34 | |
883 | 20,069 | |
6.0% | 0.3% | |
9.8 | 8.8 | |
6 days ago | 3 days ago | |
Python | Go | |
Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
canopy
- FLaNK AI Weekly for 29 April 2024
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How to choose the right type of database
Pinecone: A scalable vector database service that facilitates efficient similarity search in high-dimensional spaces. Ideal for building real-time applications in AI, such as personalized recommendation engines and content-based retrieval systems.
- Show HN: R2R – Open-source framework for production-grade RAG
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Using Stripe Docs in your RAG pipeline with LlamaIndex
In this post we’ll build a Python script that uses StripeDocs Reader, a loader on LlamaIndex, that creates vector embeddings of Stripe's documentation in Pinecone. This allows a user to ask questions about Stripe Docs to an LLM, in this case OpenAI, and receive a generated response.
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7 Vector Databases Every Developer Should Know!
Pinecone is a managed vector database service that simplifies the process of building and scaling vector search applications. It offers a simple API for embedding vector search into applications, providing accurate, scalable similarity search with minimal setup and maintenance.
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Using Vector Embeddings to Overengineer 404 pages
In case of AIMD, I am doing this all in-memory, but you could also do this in a database (e.g. Pinecone). It all depends on how much data you have and how much compute you have available.
- Pinecone: Build Knowledgeable AI
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How Modern SQL Databases Are Changing Web Development - #4 Into the AI Era
A RAG implementation's quality and performance highly depend on the similarity-based search of embeddings. The challenge arises from the fact that embeddings are usually high-dimensional vectors, and the knowledge base may have many documents. It's not surprising that the popularity of LLM catalyzed the development of specialized vector databases like Pinecone and Weaviate. However, SQL databases are also evolving to meet the new challenge.
- FLaNK Stack Weekly 11 Dec 2023
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Embracing Modern Python for Web Development
In the dynamic world of web development, Python has emerged as a dominant force, especially in backend development – the primary focus of this blog post. Although it's worth mentioning that there are ongoing efforts to use Python for the frontend as well, like Reflex (previously known as Pynecone, they presumably had to change their name because of Pinecone vector database), which even garnered support from Y Combinator. Samuel Colvin (creator of Pydantic) is also working on FastUI (he literally just released the first version in December 2023).
dgraph
- DGraph – GraphQL Database
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How to choose the right type of database
Dgraph: A distributed and scalable graph database known for high performance. It's a good fit for large-scale graph processing, offering a GraphQL-like query language and gRPC API support.
- Is Dgraph dead? (should I continue using it)
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Database Review: Top Five Missing Features from Database APIs
Dgraph (GraphQL, DQL)
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Learning Graph Database data design & data modeling
Have you tried dgraph.io?
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Getting Started with Serverless Edge - Exploring the Options
DGraph – A distributed GraphQL database with a graph backend.
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Fluree DB - A datomic like database that I just discovered
How does it compare to, say grakn (renamed https://vaticle.com/, I think?), or draph (https://dgraph.io/), or Ontotext's GraphDB (https://www.ontotext.com/products/graphdb/), or Datomic?
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GKE with Consul Service Mesh
Consul Connect service mesh has a higher memory footprint, so on a small cluster with e5-medium nodes (2 vCPUs, 4 GB memory), you will only be able to support a maximum of 6 side-car proxies. In order to get an application like Dgraph working, which will have 6 nodes (3 Dgraph Alpha pods and 3 Dgraph Zero pods) for high availability along with at least one client, a larger footprint with more robust Kubernetes worker nodes were required.
- Show HN: We have built a benchmark platform for graph databases
- What's the big deal about key-value databases like FoundationDB ands RocksDB?
What are some alternatives?
ragna - RAG orchestration framework ⛵️
cockroach - CockroachDB - the open source, cloud-native distributed SQL database.
tiger - Open Source LLM toolkit to build trustworthy LLM applications. TigerArmor (AI safety), TigerRAG (embedding, RAG), TigerTune (fine-tuning)
Hasura - Blazing fast, instant realtime GraphQL APIs on your DB with fine grained access control, also trigger webhooks on database events.
simple-pgvector-python - An Abstraction Using a similar API to Pinecone but implemented with pgvector python
spicedb - Open Source, Google Zanzibar-inspired permissions database to enable fine-grained access control for customer applications
deeplake - Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai
tidb - TiDB is an open-source, cloud-native, distributed, MySQL-Compatible database for elastic scale and real-time analytics. Try AI-powered Chat2Query free at : https://tidbcloud.com/free-trial
mlx-examples - Examples in the MLX framework
TinyGo - Go compiler for small places. Microcontrollers, WebAssembly (WASM/WASI), and command-line tools. Based on LLVM.
tonic_validate - Metrics to evaluate the quality of responses of your Retrieval Augmented Generation (RAG) applications.
go-mysql - a powerful mysql toolset with Go