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.
Delegate anything. It comes back done.
Blazing fast, instant realtime GraphQL APIs on all your data with fine grained access control, also trigger webhooks on database events.
Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
Modern and easy to use SQL client for MySQL, Postgres, SQLite, SQL Server, and more. Linux, MacOS, and Windows.
Open-source data movement for ELT pipelines and AI agents — from APIs, databases & files to warehouses, lakes, and AI applications. Both self-hosted and Cloud.
📊 Cube Core is open-source semantic layer for AI, BI and embedded analytics
MCP Toolbox for Databases is an open source MCP server for databases.
GenBI (Generative BI) for AI agents, an open-source, governed text-to-SQL through an open context layer that turns natural-language questions into trusted dashboards, charts, and SQL across 20+ data sources, such as BigQuery, Snowflake, PostgreSQL, ClickHouse, Amazon Redshift, Databricks and more.
Open Source Feature Flags, Experimentation, and Product Analytics
Data pipelines for cloud config and security data. Build cloud asset inventory, CSPM, FinOps, and vulnerability management solutions. Extract from AWS, Azure, GCP, and 70+ cloud and SaaS sources.
Jitsu is an open-source Segment alternative. Fully-scriptable data ingestion engine for modern data teams. Set-up a real-time data pipeline in minutes, not days
Privacy and Security focused Segment-alternative, in Golang and React
Dashboards and notebooks in a single place. Create powerful and flexible dashboards using code, or build beautiful Notion-like notebooks and share them with your team.
tbls is a CI-Friendly tool to document a database, written in Go.
🍟 a notebook sql client. what you get when have a lot of sequels.
ingestr is a CLI tool to copy data between any databases with a single command seamlessly.
Fast, Simple and a cost effective tool to replicate data from Postgres to Data Warehouses, Queues and Storage
Released May 19, 2010