{"categories":[{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/8"},{"label":"Database","url":"https://skillfed.io/packages/category/database/2"},{"label":"Front-Ends","url":"https://skillfed.io/packages/category/database-front-ends"},{"label":"Database Engines/Servers","url":"https://skillfed.io/packages/category/database-database-engines-servers"}],"enrichment":{"capability":"dbt adapter that enables data transformation workflows on Vertica databases, connecting dbt projects to Vertica via the vertica-python client.","skillfed_tags":["dbt-adapter","data-transformation","vertica"],"use_cases":["Build incremental fact tables in Vertica using dbt's merge or delete+insert strategies to avoid full table rewrites.","Run dbt tests and documentation generation on Vertica models as part of a data quality and governance workflow.","Orchestrate multi-step SQL transformations in Vertica using dbt's DAG and dependency resolution.","Execute dbt unit tests directly against Vertica to validate transformation logic before production deployment.","Manage Vertica schema evolution and snapshots using dbt's snapshot feature for slowly-changing dimensions."],"what_it_does":"dbt-vertica is a dbt adapter that bridges dbt (a data transformation tool) and Vertica databases. It uses vertica-python to handle the connection layer, allowing you to write dbt models, tests, and documentation that execute as SQL transformations directly in Vertica. The adapter supports most core dbt features including table, view, and incremental materializations with multiple merge strategies, snapshots, seeds, tests, and unit testing.\n\nYou install it once alongside dbt-core, configure a profiles.yml file with your Vertica connection details (host, port, credentials, database, schema), and then use standard dbt commands (dbt run, dbt test, dbt build) to orchestrate your data pipeline. The adapter handles the translation of dbt's transformation logic into Vertica-native SQL, managing incremental updates, transaction control, and multi-threaded execution.","worth_installing":"Yes, if you use Vertica and dbt. The adapter is production-stable (Development Status 5), actively maintained, has no known vulnerabilities, and supports most dbt core features needed for typical data transformation workflows. Install friction is low. The only caveat is that external tables are untested and snapshot check_cols are not supported\u2014verify these gaps don't block your use case."},"id":"dbt-vertica","links":{"html":"https://skillfed.io/packages/dbt-vertica","md":"https://skillfed.io/packages/dbt-vertica.md","pypi":"https://pypi.org/project/dbt-vertica/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-07","license_spdx":null,"license_treatment":"permissive","name":"dbt-vertica","python_support":"supports_current","summary":"Official vertica adapter plugin for dbt (data build tool)"},"popularity":{"monthly_downloads":799853,"position":5025,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.8.6"}