Anoncheg<p>Part1: <a href="https://techhub.social/tags/dailyreport" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>dailyreport</span></a> <a href="https://techhub.social/tags/powerbi" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>powerbi</span></a> <a href="https://techhub.social/tags/datawarehouse" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>datawarehouse</span></a> <a href="https://techhub.social/tags/dwh" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>dwh</span></a> <a href="https://techhub.social/tags/postgresql" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>postgresql</span></a><br> <a href="https://techhub.social/tags/python" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>python</span></a><br>At this week I installed PowerBI and connect it to remote<br> PostgreSQL.<br>I asked AI to compare open-source data sources for<br> PowerBI and compare them by:<br>- Ease of Setup on Linux: SQLite > PostgreSQL > MySQL ><br> Redis > MongoDB<br>- Performance:<br> + For large datasets: MongoDB > PostgreSQL > MySQL ><br> Redis > SQLite.<br> + For real-time operations: Redis > MongoDB > MySQL ><br> PostgreSQL > SQLite.</p><p>For PostgreSQL I prepare data in Python script that use:<br>- pandas - for coverting types to datetime and numeric<br>- sqlalchemy - for simplifying type converstion<br>- asyncpg - sqlalchemy backend to connect to PostgreSQL</p>