Source Catalog Agent: Architecture, Integrations, & Security

Enterprise metadata cataloging requires robust coordination, wide-ranging integrations, and strict security designs. The Source Catalog Agent provides a foundational layer for other Datapunkt agents, interfaces directly with standard industry systems, and operates within a zero-storage security architecture to satisfy corporate security standards.

Multi-Agent Architecture & Cooperation

Within the Datapunkt ecosystem, agents do not work in isolation. The Source Catalog Agent operates as the primary ingress point, discovering and registering metadata that downstream agents rely on:

• Data Lineage Agent: Uses the schemas and column IDs mapped by the Source Catalog Agent to construct field-level dependencies.
• Data Quality Agent: References the catalog profiles to set baseline rules (such as expected null rates, uniqueness, and value distributions) for data quality checks.
• Transformation Agent: Uses the generated master schemas as source contracts, generating SQL, Python, or Spark code to clean and restructure data.
• Data Architect & Product Agents: Consume standard definitions to assemble higher-level data products and conceptual graphs.

By using the Source Catalog Agent as the single entry point, you prevent downstream agents from running redundant scans. This reduces read loads on production systems.

Integrations

The Source Catalog Agent fits cleanly into diverse setups by supporting standard ingestion and destination channels:

Ingestion Methods

• Relational Databases (JDBC / ODBC): Connects to relational platforms like PostgreSQL, MySQL, Oracle, and Microsoft SQL Server to extract table lists, column types, and constraints.
• Event Streams (Apache Kafka / AMQP): Connects to Kafka brokers or AMQP message queues (e.g. RabbitMQ) to map schemas from dynamic message payloads.
• Columnar & Semi-Structured Formats (Parquet / JSON / AVRO): Parses physical files residing in object storage, mapping nested attributes to standard models.
• API & Processing Logs (REST API / Open Lineage): Collects operational metadata directly from REST endpoints and open-standard lineages.

Downstream Destinations

Once metadata is structured, the agent publishes it to:

• Cloud Data Warehouses: Syncs metadata models with Google BigQuery, Snowflake, and Amazon Redshift.
• Enterprise Catalogs: Exports details to open-source or custom corporate catalogs.
• Operational Databases: Writes mapping properties back to transactional tables to support custom administrative systems.

Security, Compliance, and Data Residency

Data governance demands strict security controls. The Source Catalog Agent is built from the ground up to protect raw data assets and maintain corporate compliance.

Zero-Storage Architecture

A core design principle of the Source Catalog Agent is that no customer data is stored on Datapunkt's servers. The agent accesses schemas, names, and distributions dynamically, but it does not copy, persist, or extract the underlying records. Because row-level data never leaves your network perimeter, data breach risks and compliance exposures are eliminated.

Enterprise Compliance Support

The agent is designed to support major data privacy regulations:

• GDPR: Simplifies compliance by identifying where Personally Identifiable Information (PII) is stored, supporting data access and erasure operations.
• CCPA: Maps consumer data locations across systems, helping you fulfill regulatory requests.
• SOC 2 & ISO 27001: Fits into enterprise security models through credential isolation, encrypted storage, and detailed access logging.

Authentication & Access Controls

The agent connects to your infrastructure using industry-standard protocols to prevent unauthorized access:

• Service Accounts: Runs via highly restricted service accounts limited to read-only database system catalogs.
• OAuth 2.0: Employs secure token exchange for cloud sources, avoiding password exposure.

Multi-Region Data Residency

To meet local regulatory requirements, you can choose the geographical region where the agent instance and its temporary processing metadata reside:

• United States (US)
• Europe (EU)
• Asia-Pacific (APAC)
• Customer-Specified Location (for custom enterprise environments)

Benefits: What Makes It Good?

• Reduces Infrastructure Load: Single scan ingestion supplies metadata to multiple downstream agents, saving network bandwidth and database processing power.
• Zero Trust Security Model: Operates on a metadata-only basis, ensuring your customer records never cross network boundaries.
• Standardized Integrations: Resolves format mismatches by bringing legacy JDBC databases and modern Kafka/AMQP messaging queues under a single schema definition.
• Flexible Residency Controls: Conforms to geographic data storage mandates, providing localized data boundaries.