AWS Glue DataBrew vs Flyte
Overview
Share your Stack
Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.
CLI (Node.js)
Manual
Detailed Comparison
It is a new visual data preparation tool that makes it easy for data analysts and data scientists to clean and normalize data to prepare it for analytics and machine learning. You can choose from over 250 pre-built transformations to automate data preparation tasks, all without the need to write any code. You can automate filtering anomalies, converting data to standard formats, and correcting invalid values, and other tasks. After your data is ready, you can immediately use it for analytics and machine learning projects. You only pay for what you use - no upfront commitment. | It is an open-source, Kubernetes-native workflow orchestrator implemented in Go. It enables highly concurrent, scalable, and reproducible workflows for data processing, machine learning and analytics. |
Evaluate the quality of your data by profiling it to understand data patterns and detect anomalies, connect data directly from your data lake, data warehouses, and databases;
Choose from over 250 built-in transformations to visualize, clean, and normalize your data with an interactive, point-and-click visual interface;
Visually map the lineage of your data to understand the various data sources and transformation steps that the data has been through;
Automate data cleaning and normalization tasks by applying saved transformations directly to new data as it comes into your source system | Write locally, execute remotely;
Scale as fast as your imagination;
Give the power back to data practitioners and scientists;
Create extremely flexible data and ML workflows |
Statistics | |
GitHub Stars - | GitHub Stars 6.6K |
GitHub Forks - | GitHub Forks 757 |
Stacks 14 | Stacks 2 |
Followers 13 | Followers 2 |
Votes 0 | Votes 0 |
Integrations | |
What are some alternatives to AWS Glue DataBrew, Flyte?
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
Pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.
Keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
Kubeflow
The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.
TensorFlow.js
Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API
NumPy
Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
Polyaxon
An enterprise-grade open source platform for building, training, and monitoring large scale deep learning applications.
Streamlit
It is the app framework specifically for Machine Learning and Data Science teams. You can rapidly build the tools you need. Build apps in a dozen lines of Python with a simple API.
