Scale your data, not your process: Welcome to the Blaze ecosystem
summary
Blaze claims a single API that queries CSV, Postgres, MongoDB, HDF5, BColz or Spark without reauthoring code, uses Datashape for types, Odo to migrate between S3 CSV and Postgres and Dask to run lazy evaluation on chunked arrays so gigabytes fit in memory and terabytes run in parallel. A Blaze server exposes the same queries over JSON and Odo builds a conversion graph under the hood; demos show queries and conversions executing end to end.
AI-written summary · about
chapters (7)
- 0:00Introduction
- 2:07Areas of data science
- 6:04Tools
- 10:31Ecosystem
- 15:35Place
- 26:45Resources
- 30:46Blaze vs other Python libraries
related talks
33mBlaze: crunching data in different formats through a single API.
50mDesigning a scalable data platform based on Apache Spark/Iceberg
17mDemocratising data analytics
49mData Platform Architecture, Evolution, and Philosophy
36mFlare: Optimizing Apache Spark for Scale-Up Architectures and Medium-Size Data
32mScalable Python and SQL Data Engineering without Migraines
31mThe PyData map: Presenting a map of the landscape of PyData tools
23mAcceleratinag Data Science and Machine Learning with Snowflake DataTech