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The Airflow integration consumes OpenLineage metadata from Airflow.
The BigQuery integration synchronizes metadata from your BigQuery datawarehouse into the data lineage graph.
Upload CSVs into the data lineage graph.
The Cube integration synchronizes your Cubes, dimensions, and measures with Grai. In this way you can quickly identify which data is being used in your Cube instance.
The Dagster integration uses OpenLineage to collect and send metadata to Grai.
Upload Feather files into the data lineage graph.
The Fivetran integration synchronizes your Fivetran connection metadata into the lineage graph.
The Flink integration uses OpenLineage to collect and send metadata to Grai.
The Great Expectations integration uses OpenLineage to collect and send metadata to Grai.
The Keboola integration uses OpenLineage to collect and send metadata to Grai.
The Looker integration synchronizes your Dashboards and LookML from Looker into Grai In this way you can quickly identify which data is being used by your BI tools, which data is not, and more.
The Metabase integration synchronizes your Metabase Question metadata into the lineage graph. In this way you can quickly identify which data is being used by your BI tools, which data is not, and more.
The SQL Server integration synchronizes metadata from your SQL Server databases into the data lineage graph.
The MySQL integration synchronizes metadata from your MySQL databases into the data lineage graph.
The OpenLineage integration consumes OpenLineage metadata from various systems.
Upload Parquet files into the data lineage graph.
The postgres integration can be run as a standalone python library to extract data lineage from your instance of Postgres.
The Redshift integration can be run as a standalone python library to extract data lineage from your instance of Redshift.
The Snowflake integration synchronizes metadata from your Snowflake datawarehouse into the data lineage graph.
The Spark integration uses OpenLineage to collect and send metadata to Grai.
Every aspect of Grai can be serialized to yaml. This allows you to manage your entire data lineage as code, backup your lineage in version control, or create and edit nodes/edges in code.
The dbt integration updates metadata from your dbt manifest into the data lineage graph.
The dbt Cloud integration synchronizes your dbt metadata into the lineage graph.
Airbyte enables you to build data pipelines and replicate data from a source to a destination. You can configure how frequently the data is synced, what data is replicated, and how the data is written to in the destination.
Amazon Aurora (Aurora) is a fully managed relational database engine that's compatible with MySQL and PostgreSQL
Iceberg is a high-performance format for huge analytic tables. Iceberg brings the reliability and simplicity of SQL tables to big data, while making it possible for engines like Spark, Trino, Flink, Presto, Hive and Impala to safely work with the same tables, at the same time.
Kedro is an open-source Python framework hosted by the Linux Foundation (LF AI & Data). Kedro uses software engineering best practices to help you build production-ready data science code.
MongoDB is a non-relational document database that provides support for JSON-like storage. The MongoDB database has a flexible data model that enables you to store unstructured data, and it provides full indexing support, and replication with rich and intuitive APIs.
Stitch is a cloud-first, open source platform for rapidly moving data. A simple, powerful ETL service, Stitch connects to all your data sources – from databases like MySQL and MongoDB, to SaaS applications like Salesforce and Zendesk – and replicates that data to a destination of your choosing.
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