Terality Docs
  • What is Terality?
  • Documentation
    • Quickstart
      • Setup
      • Tutorial
      • Next steps
    • User guide
      • Supported configurations
      • User dashboard
      • Importing and exporting data
        • Reading/writing to storage
        • Reading from multiple files
        • Writing to multiple files
        • Storage services
        • Data formats
        • From/to pandas
      • .apply() and passing callables
      • Caching
      • Best practices and anti-patterns
      • Upgrading your client version
      • Client configuration (CLI)
      • Support for external packages
      • Advanced topics
        • Data mutability and ownership: Terality vs pandas
    • API Reference
      • Conversion from/to pandas
      • Write to multiple files
    • Deploy Terality in your own AWS account
    • Releases
  • FAQ
    • Differences with
      • Terality and Pandas
      • Terality vs Spark
      • Terality vs Dask
    • Pricing
    • Security
    • Support & contact
    • Common setup issues
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  1. FAQ
  2. Differences with

Terality and Pandas

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Last updated 3 years ago

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Because Pandas doesn't scale well, we have built Terality to enable data scientists and engineers to scale Pandas just by changing the import line in their notebook or IDE.

Terality enables to run Pandas code 10x faster, even on 100 of GBs of data, in a full serverless way. No infrastructure setup is needed.

Differences between Terality and Pandas

Pandas (locally)

Terality

Syntax

Pandas

Pandas

Ideal dataset's size

Less than 1GB

1GB to 100GBs

Parallelization on multiple cores for lightning speed

No

Yes (10-100x faster than Pandas)

Memory available

Local Memory

Virtually unlimited, fully managed

Read our Benchmark Blog article

https://www.terality.com/post/benchmark-terality-vs-pandas-10x