Vertica

About Vertica

A distributed, MPP columnar database designed for large-scale analytics workloads. Vertica offers extensive analytics SQL, machine learning capabilities, and high compression ratios for efficient storage of massive datasets.

Key Features

• 1Columnar MPP database optimized for large-scale analytical workloads
• 2Automatic data encoding and compression for storage efficiency
• 3Projections (materialized views) pre-sort and encode data for query patterns
• 4In-database machine learning with Python UDFs via Vertica ML
• 5Eon Mode for separation of compute and storage on cloud object storage

How Python Data Engineers Use Vertica

Python data engineers use `vertica-python` or the SQLAlchemy Vertica dialect to connect Vertica to pandas-based pipelines. Engineers load bulk data via COPY from S3 or local files using the Python client's `copy_local_input_stream()` method, and run analytical SQL queries that Vertica executes across its MPP nodes for sub-second aggregation on terabyte-scale datasets.