BigQuery topic
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.
redash
Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
graphql-engine
Blazing fast, instant realtime GraphQL APIs on your DB with fine grained access control, also trigger webhooks on database events.
cube
📊 Cube — The Semantic Layer for Building Data Applications
gcp-essentials
Sample code and notes for my GCP courses on LinkedIn Learning
ethereum-etl
Python scripts for ETL (extract, transform and load) jobs for Ethereum blocks, transactions, ERC20 / ERC721 tokens, transfers, receipts, logs, contracts, internal transactions. Data is available in Go...
logica
Logica is a logic programming language that compiles to SQL. It runs on Google BigQuery, PostgreSQL and SQLite.
beast
[Deprecated] Load data from Kafka to any data warehouse. BQ sink is being supported in Firehose now. https://github.com/odpf/firehose
growthbook
Open Source Feature Flagging and A/B Testing Platform
sqlpad
Web-based SQL editor. Legacy project in maintenance mode.