A database transport provides a standardized mechanism for connecting to, interacting with, and exchanging data between your system and external database servers. It abstracts the underlying communication details, allowing applications to read from and write to databases in a consistent and configurable manner.
Database transports support both relational (SQL) and non-relational (NoSQL) database paradigms, enabling flexibility in how data is structured, stored, and accessed:
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SQL databases use a structured, schema-based model with tables, relationships, and ACID-compliant transactions, ensuring strong consistency and data integrity.
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NoSQL databases use flexible, schema-less or semi-structured models, often optimized for horizontal scalability, high availability, and eventual consistency.
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Snowflake databases use a cloud-based, columnar model optimized for scalable analytics, elastic compute, and high-performance querying across large datasets
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Databricks databases use a lakehouse model that combines data lake flexibility with warehouse-style analytics, supporting large-scale data engineering, streaming, machine learning, and collaborative analytics workflows.
Through database transports, systems can integrate with a wide range of data backends, regardless of whether the data model is tabular, document-based, key-value, columnar, or graph-oriented.
What's Inside
This section provides guidance on configuring database transports, establishing connections to supported database systems and performing data operations across both relational and non-relational environments.