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NumPy vs Pentaho Data Integration: What are the differences?
Developers describe NumPy as "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. On the other hand, Pentaho Data Integration is detailed as "Easy to Use With the Power to Integrate All Data Types". 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.
NumPy and Pentaho Data Integration belong to "Data Science Tools" category of the tech stack.
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.
Instacart, Twilio SendGrid, and Catho are some of the popular companies that use NumPy, whereas Pentaho Data Integration is used by WhoseBill Limited, Lionix, and Trixlog. NumPy has a broader approval, being mentioned in 87 company stacks & 251 developers stacks; compared to Pentaho Data Integration, which is listed in 14 company stacks and 6 developer stacks.
Pros of NumPy
- Great for data analysis10
- Faster than list4
Pros of Pentaho Data Integration
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What is NumPy?
What is Pentaho Data Integration?
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