canopy
RocksDB
canopy | RocksDB | |
---|---|---|
14 | 43 | |
883 | 27,424 | |
6.0% | 0.8% | |
9.8 | 9.8 | |
7 days ago | 2 days ago | |
Python | C++ | |
Apache License 2.0 | GNU General Public License v3.0 only |
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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).
RocksDB
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How to choose the right type of database
RocksDB: A high-performance embedded database optimized for multi-core CPUs and fast storage like SSDs. Its use of a log-structured merge-tree (LSM tree) makes it suitable for applications requiring high throughput and efficient storage, such as streaming data processing.
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Fast persistent recoverable log and key-value store
[RocksDB](https://rocksdb.org/) isn’t a distributed storage system, fwiw. It’s an embedded KV engine similar to LevelDB, LMDB, or really sqlite (though that’s full SQL, not just KV)
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The Hallucinated Rows Incident
To output the top 3 rocks, our engine has to first store all the rocks in some sorted way. To do this, we of course picked RocksDB, an embedded lexicographically sorted key-value store, which acts as the sorting operation's persistent state. In our RocksDB state, the diffs are keyed by the value of weight, and since RocksDB is sorted, our stored diffs are automatically sorted by their weight.
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In-memory vs. disk-based databases: Why do you need a larger than memory architecture?
The in-memory version of Memgraph uses Delta storage to support multi-version concurrency control (MVCC). However, for larger-than-memory storage, we decided to use the Optimistic Concurrency Control Protocol (OCC) since we assumed conflicts would rarely happen, and we could make use of RocksDB’s transactions without dealing with the custom layer of complexity like in the case of Delta storage.
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Local file non relational database with filter by value
I was looking at https://github.com/facebook/rocksdb/ but it seems to not allow queries by value, as my last requirmenet.
- Rocksdb over network
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How RocksDB Works
Tuning RocksDB well is a very very hard challenge, and one that I am happy to not do day to day anymore. RocksDB is very powerful but it comes with other very sharp edges. Compaction is one of those, and all answers are likely workload dependent.
If you are worried about write amplification then leveled compactions are sub-optimal. I would try the universal compaction.
- https://github.com/facebook/rocksdb/wiki/Universal-Compactio...
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What are the advantages of using Rust to develop KV databases?
It's fairly challenging to write a KV database, and takes several years of development to get the balance right between performance and reliability and avoiding data loss. Maybe read through the documentation for RocksDB https://github.com/facebook/rocksdb/wiki/RocksDB-Overview and watch the video on why it was developed and that may give you an impression of what is involved.
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We’re the Meilisearch team! To celebrate v1.0 of our open-source search engine, Ask us Anything!
LMDB is much more sain in the sense that it supports real ACID transactions instead of savepoints for RocksDB. The latter is heavy and consumes a lot more memory for a lot less read throughput. However, RocksDB has a much better parallel and concurrent write story, where you can merge entries with merge functions and therefore write from multiple CPUs.
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Google's OSS-Fuzz expands fuzz-reward program to $30000
https://github.com/facebook/rocksdb/issues?q=is%3Aissue+clic...
Here are some bugs in JeMalloc:
What are some alternatives?
ragna - RAG orchestration framework ⛵️
LevelDB - LevelDB is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values.
tiger - Open Source LLM toolkit to build trustworthy LLM applications. TigerArmor (AI safety), TigerRAG (embedding, RAG), TigerTune (fine-tuning)
LMDB - Read-only mirror of official repo on openldap.org. Issues and pull requests here are ignored. Use OpenLDAP ITS for issues.
simple-pgvector-python - An Abstraction Using a similar API to Pinecone but implemented with pgvector python
SQLite - Unofficial git mirror of SQLite sources (see link for build instructions)
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
sled - the champagne of beta embedded databases
mlx-examples - Examples in the MLX framework
ClickHouse - ClickHouse® is a free analytics DBMS for big data
tonic_validate - Metrics to evaluate the quality of responses of your Retrieval Augmented Generation (RAG) applications.
TileDB - The Universal Storage Engine