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  1. Stackups
  2. AI
  3. Development & Training Tools
  4. Data Science Tools
  5. Hex.tech vs Metaflow

Hex.tech vs Metaflow

OverviewComparisonAlternatives

Overview

Metaflow
Metaflow
Stacks16
Followers51
Votes0
GitHub Stars9.6K
Forks930
Hex.tech
Hex.tech
Stacks4
Followers3
Votes0

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Detailed Comparison

Metaflow
Metaflow
Hex.tech
Hex.tech

It is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. It was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning.

It is a modern Data Workspace. It makes it easy to connect to data, analyze it in collaborative SQL and Python-powered notebooks, and share work as interactive data apps and stories.

End-to-end ML Platform; Model with your favorite tools; Powered by the AWS cloud; Battle-hardened at Netflix
A new way to notebook; SQL superpowers; Stunning visualizations; Infinite data scale
Statistics
GitHub Stars
9.6K
GitHub Stars
-
GitHub Forks
930
GitHub Forks
-
Stacks
16
Stacks
4
Followers
51
Followers
3
Votes
0
Votes
0
Integrations
No integrations available
Clickhouse
Clickhouse
Dagster
Dagster
Google BigQuery
Google BigQuery
dbt
dbt
Python
Python
Snowflake
Snowflake
GitHub
GitHub
Materialize
Materialize
GitLab
GitLab
Airflow
Airflow

What are some alternatives to Metaflow, Hex.tech?

Pandas

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.

NumPy

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.

PyXLL

PyXLL

Integrate Python into Microsoft Excel. Use Excel as your user-facing front-end with calculations, business logic and data access powered by Python. Works with all 3rd party and open source Python packages. No need to write any VBA!

SciPy

SciPy

Python-based ecosystem of open-source software for mathematics, science, and engineering. It contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.

Dataform

Dataform

Dataform helps you manage all data processes in your cloud data warehouse. Publish tables, write data tests and automate complex SQL workflows in a few minutes, so you can spend more time on analytics and less time managing infrastructure.

PySpark

PySpark

It is the collaboration of Apache Spark and Python. it is a Python API for Spark that lets you harness the simplicity of Python and the power of Apache Spark in order to tame Big Data.

Anaconda

Anaconda

A free and open-source distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. Package versions are managed by the package management system conda.

Dask

Dask

It is a versatile tool that supports a variety of workloads. It is composed of two parts: Dynamic task scheduling optimized for computation. This is similar to Airflow, Luigi, Celery, or Make, but optimized for interactive computational workloads. Big Data collections like parallel arrays, dataframes, and lists that extend common interfaces like NumPy, Pandas, or Python iterators to larger-than-memory or distributed environments. These parallel collections run on top of dynamic task schedulers.

Pentaho Data Integration

Pentaho Data Integration

It enable users to ingest, blend, cleanse and prepare diverse data from any source. With visual tools to eliminate coding and complexity, It puts the best quality data at the fingertips of IT and the business.

StreamSets

StreamSets

An end-to-end data integration platform to build, run, monitor and manage smart data pipelines that deliver continuous data for DataOps.

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