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Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python. | It is a non-typical object-relational mapping library in Python for asyncio, built on top of SQLAlchemy core and asyncpg, aiming for explicitness and productivity. |
All behind the scenes- Your queries can execute asynchronously in the background, and can be polled for status.;Import data with ease- Bulk load your data using Google Cloud Storage or stream it in bursts of up to 1,000 rows per second.;Affordable big data- The first Terabyte of data processed each month is free.;The right interface- Separate interfaces for administration and developers will make sure that you have access to the tools you need. | Run SQLAlchemy core queries on asyncpg;
Optional non-intrusive objective API;
Advanced loader system to assemble objects from row results;
Support the SQLAlchemy ecosystem like Alembic;
Built-in support for context, lazy connection and more;
Extensions to integrate with Starlette/FastAPI, aiohttp, Tornado and more |
Statistics | |
GitHub Stars - | GitHub Stars 2.7K |
GitHub Forks - | GitHub Forks 150 |
Stacks 1.8K | Stacks 3 |
Followers 1.5K | Followers 9 |
Votes 152 | Votes 0 |
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