AI · alternatives · 2026
24 alternatives to A lighting-fast and developer-friendly Federated Learning SDK
Hello everyone We have been working for a couple of years now on MetisFL, a federated learning framework that allows developers to federate their machine learning workflows and train their models across distributed datasets without having to collect the data in a centralized location. Since the project is now transitioning to a public phase, we are actively encouraging developers, researchers and data scientists to experiment with the framework and contribute to the codebase. Thank you in advance!
MetisFL is a federated learning framework that enables developers to train machine learning models across distributed datasets without centralizing data. The SDK allows machine learning workflows to be federated… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. A lighting-fast and developer-friendly Federated Learning SDK launched in 2023; newer entries below may have overtaken it.
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TensorFlow 1.0▲823Open-source machine learning library by Google
2017 · tensorflow.org · its alternatives →
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Accelerating open machine learning research with Cloud TPUs
2017 · sites.research.google · its alternatives →
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🦉⚡️Serverless, distributed vector database as an API - TimeSurgeLabs/athenadb
2024 · github.com · its alternatives →
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An Open Source Machine Learning Framework for Everyone - tensorflow/tensorflow/core/distributed_runtime at master · tensorflow/tensorflow
2016 · github.com · its alternatives →
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Supabase Vector▲398The open source backend for AI applications
2023 · supabase.com · its alternatives →
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The federated data analytics platform, loved by Pandas
2021 · its alternatives →
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:satellite: Simple and ready-to-use tutorials for TensorFlow - GitHub - instillai/TensorFlow-Course: :satellite: Simple and ready-to-use tutorials for TensorFlow
2018 · github.com · its alternatives →
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AI Infra / AI Orchestration / AI Control Plane. Contribute to polyaxon/polyaxon development by creating an account on GitHub.
2017 · github.com · its alternatives →
- 9
TensorZero▲307Hi HN! We're Gabriel & Viraj, and we're excited to open source TensorZero. To be a little cheeky, TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. 1. Integrate our model gateway 2. Send metrics or feedback 3. Unlock compounding improvements in quality, cost, and latency It enables a data & learning flywheel for LLMs by unifying: • Inference: one API for all LLMs, with <1ms P99 overhead • Observability: inference & feedback → your database • Optimization: better prompts, models, inference strategies • Experimentation:…
2025 · github.com · its alternatives →
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High-performance TensorFlow library for quantitative finance. - google/tf-quant-finance
2021 · github.com · its alternatives →
- 12
Vector space model implemented in a few lines . Contribute to felipehummel/TinySearchEngine development by creating an account on GitHub.
2011 · github.com · its alternatives →
- 13
Bring DevOps practices to your projects for automatic, reproducible, and fast machine learning.
2020 · cml.dev · its alternatives →
- 14
Hey hacker news, we launched a few weeks ago as a GPT-powered chatbot for developer docs, and quickly realized that the value of what we’re doing isn’t the chatbot itself. Rather, it’s the time we save developers by automating the extraction of data from their SaaS tools (Github, Zendesk, Salesforce, etc) and helping transform it to contextually relevant chunks that fit into GPT’s context window. A lot of companies are building prototypes with GPT right now and they’re all using some combination of Langchain/Llama Index + Weaviate/Pinecone + GPT3.5/GPT4 as their stack for…
2023 · github.com · its alternatives →
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TensorFlow Lite▲163Low-latency inference of on-device ML models
2017 · developers.google.com · its alternatives →
- 16
Open-source machine learning library by Google
2018 · tensorflow.org · its alternatives →
- 17
I am excited to announce the release of TabPFN v2, a tabular foundation model that delivers state-of-the-art predictions on small datasets in just 2.8 seconds for classification and 4.8 seconds for regression compared to strong baselines tuned for 4 hours. Published in Nature, this model outperforms traditional methods on datasets with up to 10,000 samples and 500 features. The model is available under an open license: a derivative of the Apache 2 license with a single modification, adding an enhanced attribution requirement inspired by the Llama 3 license:…
2025 · nature.com · its alternatives →
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💥 Fast State-of-the-Art Tokenizers optimized for Research and Production - huggingface/tokenizers
2020 · github.com · its alternatives →
- 19
Hey HN, I am the founder of Tensorlake. Prototyping LLM applications have become a lot easier, building decision making LLM applications that work on constantly updating data is still very challenging in production settings. The systems engineering problems that we have seen people face are - 1. Reliably process ingested content in real time if the application is sensitive to freshness of information. 2. Being able to bring in any kind of model, and run different parts of the pipeline on GPUs and CPUs. 3. Fault Tolerance to ingestion spike, compute infrastructure failure. 4. Scaling compute,…
2024 · getindexify.ai · its alternatives →
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Hey HN! We are building Epsilla (https://github.com/epsilla-cloud/vectordb), an open-source, self-hostable vector database for semantic similarity search that specializes in low query latency. When do we need a vector database? For example, GPT-3.5 has a 16k context window limit. If we want to let it answer a question about a 300 page book, we cannot put the whole book content into the context. We have to choose the sections of the book that are most relevant to the question. Vector database is specialized at ranking and picking the most relevant content from a large pool…
2023 · github.com · its alternatives →
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integrate.ai▲80Extend your product to train ML models on distributed data
2022 · integrate.ai · its alternatives →
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We are the developers of an open-source package Metaflow that we started at Netflix. Metaflow provides a human-friendly interface to the full stack of ML infrastructure, including data access, compute, workflow orchestration, and versioning. It is used by hundreds of companies across industries. Over the past years, we have seen that there are two major stumbling blocks for folks who want to learn to build real-world ML applications: 1) Setting up the full infrastructure stack in the cloud costs time and money. The investment is worth it once you know what you want to do, but that's not…
2023 · outerbounds.com · its alternatives →
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🃏 A distributed unique ID generator inspired by Twitter's Snowflake. - bahlo/sonyflake-rs
2020 · github.com · its alternatives →
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built a tiny pytorch clone in c after going through prof. vijay janapa reddi's mlsys book: mlsysbook.ai/tinytorch/ perfect for learning how ml frameworks work under the hood :)
Dec 2025 · github.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →