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If you are looking to explore and understand your database (relational or document), Azimutt is the tool you need. It's the first entity relationship diagram built to handle big database schema (up to 1000 tables) with dedicated features: search, find path and even schema analysis to keep it consistent.
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Azimutt's answer:
Azimutt is mainly targeted at developers working with databases, allowing them to easily explore and understand them by either importing the schema or connecting to a live instance.
As it's quite easy to use, we have seen other profile such as product owners, engineering managers and even CFOs using it to better understand the product they build or extract meaningful data on their own ^^
Azimutt's answer:
Early 2021 I joined Doctolib, a health startup very successful in France, and discovered their big Ruby on Rails monolith backed by a large PostgreSQL database with more than 700 business tables (more then 1300 in total). As an architect I worked with several teams and needed to understand their models but neither Ruby, Rails or the structure.sql were very helpful for such a big app. So I looked for a tool but they all failed with such a large database, so after a few month and tens of tools tested, I decided to build my own: Azimutt. Now it has evolved a lot and we are still very active to enable new usages every months. I believe it's a solid product and quite unique โค๏ธ
Azimutt's answer:
From development languages, Azimutt is built with Elm/TypeScript for the frontend, Elixir/Phoenix for the backend and PostgreSQL/S3 as storage.
Azimutt's answer:
It's the only ERD able to handle databases with many tables (>1000) nicely thanks to unique features:
It's also very unique in the sense it's made to explore and understand real world databases, from development to production with larges features:
Thousands of developers already love it, give it a try, we have several samples you can try right away!
Azimutt's answer:
Azimutt is the all-in-one app to explore real world databases. If you look for very specialized features some competitors may be more suited, but if you want a versatile app to explore and understand your database, we believe no competitor come close to us.
Azimutt's answer:
Azimutt is used at Doctolib (3000 people company) and some other french scale ups I can't disclose yet.
Based on our record, Scikit-learn should be more popular than Azimutt. It has been mentiond 40 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.
Certutil.exe or notepad.exe opening an external connection lands in rare because, fleet-wide, those processes almost never egress. Tune the <= 3 threshold to your environment size. For a more principled version, score each (process, destination) pair by frequency and treat the long tail as the hunt queue, which is the same idea behind scikit-learn's rarity-based anomaly methods without the model overhead. - Source: dev.to / about 1 month ago
Pre-configured environment. A working VM or container with Jupyter, pandas, scikit-learn, and transformers already installed. Realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable lab. If the first hour of training is fighting CUDA installs, the course is not ready. - Source: dev.to / about 2 months ago
Pre-configured environment. A good course ships a VM or container with Jupyter, pandas, scikit-learn, PyTorch or transformers, and realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable lab. No setup tax. - Source: dev.to / 2 months ago
Isolation-based models: Build random decision trees that split features. Points that are isolated quickly (short average path length across trees) are anomalies. IsolationForest in scikit-learn implements this. Handles high-dimensional feature spaces without assuming a distribution. - Source: dev.to / 3 months ago
In practice, youโll want to use libraries (like scikit-learn or TensorFlow.js for more advanced modeling), but the principle remains: find what similar users enjoy, and use that as a basis for recommendations. - Source: dev.to / 5 months ago
Not mine but someone showed me this : https://azimutt.app/. - Source: Hacker News / almost 2 years ago
I just want to get a basic overview quickly. An old colleague of mine created an interactive web app that does this. We use it internally and I find it super useful. Supports SQLite, among others: https://azimutt.app/. - Source: Hacker News / over 2 years ago
Hello Dev.to community, I'm Sam, a proud part of a dedicated trio that built Azimutt.app. - Source: dev.to / about 3 years ago
A couple of options here: - From a database. Generate ERD by connecting to your database directly. I've used this as a quick way to generate a diagram from my local or even QA DB (not prod DB for obvious security reasons). - From a schema dump file. Take a pg dump and then generate an ERD from the dump file. There are ERD tools like dbdaddy.dev and azimutt.app that support these options. Source: over 3 years ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
DrawSQL - Easy database diagrams. Create, visualize and collaborate on your database entity relationship diagrams.
NumPy - NumPy is the fundamental package for scientific computing with Python
DBDiagram.io - Free database diagrams designer for analysts & developers ๐
OpenCV - OpenCV is the world's biggest computer vision library
TablePlus - Easily edit database data and structure