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NumPy vs StreamSets: What are the differences?
What is NumPy? Fundamental package for scientific computing with Python. 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.
What is StreamSets? Where DevOps Meets Data Integration. The industry's first data operations platform for full life-cycle management of data in motion.
NumPy and StreamSets belong to "Data Science Tools" category of the tech stack.
Some of the features offered by NumPy are:
- a powerful N-dimensional array object
- sophisticated (broadcasting) functions
- tools for integrating C/C++ and Fortran code
On the other hand, StreamSets provides the following key features:
- Build Batch & Streaming Pipelines in Hours
- Map and Monitor Runtime Performance
- Protect Sensitive Data as it Arrives
NumPy is an open source tool with 11.4K GitHub stars and 3.76K GitHub forks. Here's a link to NumPy's open source repository on GitHub.
Pros of NumPy
- Great for data analysis10
- Faster than list4
Pros of StreamSets
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Cons of NumPy
Cons of StreamSets
- No user community2
- Crashes1