Namespace Relationships

Namespace relationships can be established using Polypheny's query language, which supports cross-namespace queries. This allows data from different namespaces to be joined and combined, even if they are based on different data models.

To define a relationship between two namespaces, you need to specify the namespace for each entity referenced in a query. For example, if you have a namespace customer associated with a relational data model and a namespace orders associated with a document data model, you can establish a relationship between them using a query like this:

SELECT customer.name, orders.order_date
FROM customer.customers AS c
JOIN orders.orders AS o
ON c.customer_id = o.customer_id

In this example, the customer and orders namespaces are related through a join operation, allowing data from both namespaces to be combined and analyzed together.

Managing Namespace Relationships

To manage namespace relationships effectively, it's important to consider the following best practices:

Namespace Segmentation: Segment your database into logical spaces based on the underlying data models and the relationships between them. This will help ensure that data is organized in a way that makes sense for your application and simplifies querying.
Cross-Namespace Queries: Use cross-namespace queries judiciously, as they can impact performance. Only join the necessary namespaces and limit the amount of data retrieved to what's needed for your application.
Namespace Documentation: Document the relationships between namespaces to help other developers understand the data structure and how to query it effectively.

Namespace Performance Optimization

Optimizing the performance of namespaces in Polypheny involves several strategies, including:

Indexing: Create indexes on frequently queried columns to improve query performance. This is especially important for namespaces associated with relational data models, where fixed schemas are used.
Caching: Use caching mechanisms to store frequently accessed data in memory, reducing the need for repeated database queries.
Query Optimization: Optimize queries to reduce the amount of data retrieved and minimize the impact of cross-namespace queries. This can include limiting the number of joins, using subqueries instead of joins, and filtering data as early as possible in the query.

Namespace Security

Namespaces in Polypheny offer several security features to ensure data privacy and integrity:

Data Isolation: Data within each namespace is isolated from other namespaces, ensuring that data is only accessible to those with the appropriate permissions.
Encryption: Encrypt data within namespaces to protect it from unauthorized access. Polypheny supports several encryption options, including at-rest encryption and in-transit encryption.
Access Controls: Set up access controls to manage who can access data within each namespace. This can include role-based access controls, which allow you to define permissions based on user roles, or attribute-based access controls, which allow you to define permissions based on user attributes.
Auditing: Audit namespace activity to track who is accessing data and how it is being used. This can help you detect and respond to any security incidents or data breaches.

Please update the Namespace section of the Polypheny documentation accordingly.

polypheny / Polypheny-DB

Added namespace relationships in Polypheny documentation #487

Affected Areas

Feature Description

Use Case(s)

Possible Solutions

Possible Alternatives

Namespace Relationships

Managing Namespace Relationships

Namespace Performance Optimization

Namespace Security