Google BigQuery enables companies to handle large amounts of data without having to manage infrastructure. Google’s documentation describes it as a « serverless architecture (that) lets you use SQL queries to answer your organization’s biggest questions with zero infrastructure management. BigQuery’s scalable, distributed analysis engine lets you query terabytes in seconds and petabytes in minutes. » Its client libraries allow the use of widely known languages such as Python, Java, JavaScript, and Go. Federated queries are also supported, making it flexible to read data from external sources.
📖 A highly rated canonical book on it is « Google BigQuery: The Definitive Guide », a comprehensive reference.
Another enriching read on the subject is the inside story told in the article by the founding product manager of BigQuery celebrating its 10th anniversary.
Database replication platform that leverages change data capture. Stream production data from databases to your data warehouse (Snowflake, BigQuery, Redshift, Databricks) in real-time.
Fast, Simple and a cost effective tool to replicate data from Postgres to Data Warehouses, Queues and Storage
A project for ingesting, processing, and analyzing market data using Google BigQuery as data lake and pandas for data manipulation.
Modern and easy to use SQL client for MySQL, Postgres, SQLite, SQL Server, and more. Linux, MacOS, and Windows.
BigQuery DataFrames (also known as BigFrames)
Open Source Feature Flagging and A/B Testing Platform
AI-powered information retrieval for big data
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AI Search & RAG Without Moving Your Data. Get instant answers from your company's knowledge across 100+ apps while keeping data secure. Deploy in minutes, not months.
The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.
Shapeless utilities for common data types
Enterprise data validation framework with BigQuery integration and Excel mapping support for financial services
Declarative text based tool for data analysts and engineers to extract, load, transform and orchestrate their data pipelines.
📊 Cube’s universal semantic layer platform is the next evolution of OLAP technology for AI, BI, spreadsheets, and embedded analytics
Build data pipelines with SQL and Python, ingest data from different sources, add quality checks, and build end-to-end flows.
Tools to collect and analyze CMCD v2 locally and in different cloud providers.
An elegant CLI toolkit for validating BigQuery queries, comparing schemas, and estimating costs before pushing code to production.
Released May 19, 2010