Apache Arrow VS Google BigQuery

Apache Arrow Reviews

Google BigQuery Reviews

Apache Arrow mentions (33)

• How moving from Pandas to Polars made me write better code without writing better code

  In comes Polars: a brand new dataframe library, or how the author Ritchie Vink describes it... a query engine with a dataframe frontend. Polars is built on top of the Arrow memory format and is written in Rust, which is a modern performant and memory-safe systems programming language similar to C/C++. - Source: dev.to / 2 months ago

• Time Series Analysis with Polars

  One is related to the heritage of being built around the NumPy library, which is great for processing numerical data, but becomes an issue as soon as the data is anything else. Pandas 2.0 has started to bring in Arrow, but it's not yet the standard (you have to opt-in and according to the developers it's going to stay that way for the foreseeable future). Also, pandas's Arrow-based features are not yet entirely on... - Source: dev.to / 5 months ago

• TXR Lisp

  IMO a good first step would be to use the txr FFI to write a library for Apache arrow: https://arrow.apache.org/. - Source: Hacker News / 5 months ago

• A Polars exploration into Kedro

  Polars is an open-source library for Python, Rust, and NodeJS that provides in-memory dataframes, out-of-core processing capabilities, and more. It is based on the Rust implementation of the Apache Arrow columnar data format (you can read more about Arrow on my earlier blog post “Demystifying Apache Arrow”), and it is optimised to be blazing fast. - Source: dev.to / 12 months ago

• Demystifying Apache Arrow

  Apache Arrow (Arrow for short) is an open source project that defines itself as "a language-independent columnar memory format" (more on that later). It is part of the Apache Software Foundation, and as such is governed by a community of several stakeholders. It has implementations in several languages (C++ and also Rust, Julia, Go, and even JavaScript) and bindings for Python, R and others that wrap the C++... - Source: dev.to / 12 months ago

Google BigQuery mentions (35)

• Swirl: An open-source search engine with LLMs and ChatGPT to provide all the answers you need 🌌

  Using the Galaxy UI, knowledge workers can systematically review the best results from all configured services including Apache Solr, ChatGPT, Elastic, OpenSearch, PostgreSQL, Google BigQuery, plus generic HTTP/GET/POST with configurations for premium services like Google's Programmable Search Engine, Miro and Northern Light Research. - Source: dev.to / 8 months ago

• Modern data stack: scaling people and technology at FINN

  Data Transformations: This phase involves modifying and integrating tables to generate new tables optimized for analytical use. Consider this example: you want to understand the purchasing behavior of customers aged between 20-30 in your online shop. This means you'll need to join product, customer, and transaction data to create a unified table for analytics. These data preparation tasks (e.g., joining... - Source: dev.to / 8 months ago

• Running Transformations on BigQuery using dbt Cloud: step by step

  Introduction In today's data-driven world, transforming raw data into valuable insights is crucial. This process, however, often involves complex tasks that demand efficiency, scalability, and reliability. Enter dbt Cloud—a powerful tool that simplifies data transformations on Google BigQuery. In this article, we'll take you through a step-by-step guide on how to run BigQuery transformations using dbt Cloud.... - Source: dev.to / 9 months ago

• Do I need a cloud computing–based data cloud company

  You'll want to evaluate what BigQuery has to offer and see if it makes sense for you to move over. Source: 10 months ago

• I used ChatGPT to get an Internship

  Watch the introductory videos on BigQuery on the Google Cloud Platform website (https://cloud.google.com/bigquery). Source: 10 months ago