Fauna is a distributed relational database with a document data model delivered as a cloud API. Fauna offers advanced querying capabilities, robust consistency guarantees, and comprehensive support for data operations. Developers can leverage Fauna’s strongly typed database language, FQL v10, to express complex business logic in transactions. With multi-region, active-active compute and a distributed transaction engine, Fauna ensures fast, reliable, and secure performance. Fauna provides flexible data modeling, global data access, and integrates seamlessly with various development tools and platforms. Fauna empowers developers to build new powerful applications faster, scale existing applications with confidence, and eliminates the need for server management with its serverless native approach. Fauna is designed to handle complex data models and supports real-time data synchronization across multiple devices and regions.

Fauna offers flexible pricing options to cater to the diverse needs of businesses. The cost of using Fauna primarily depends on factors such as data storage, data transfer, and request volume. For detailed information on pricing plans and to estimate costs for your specific use case, please visit our pricing page on the Fauna website.

Fauna ensures high-performance and low-latency data access by leveraging its global edge computing infrastructure. The bandwidth available to you depends on your chosen Fauna plan. We offer scalable bandwidth options to accommodate the needs of various applications. For more details on bandwidth allocation and limitations, please refer to our documentation or contact our support team.

Canceling your Fauna account is a straightforward process. Simply log in to your account and navigate to the account settings page. From there, you can find the option to cancel your subscription. If you have any questions or need assistance during the cancellation process, our dedicated support team is available to guide you through the steps.

Edge computing refers to the practice of processing and analyzing data closer to its source or the "edge" of the network, rather than sending it to a centralized cloud server. This approach brings computation and storage capabilities closer to the devices generating the data, reducing latency and improving real-time responsiveness.

In edge computing, data is processed and analyzed at or near the edge devices, such as IoT devices, sensors, or edge servers, rather than being sent to a central data center. By bringing computation closer to the data source, edge computing minimizes network latency and bandwidth usage, allowing for faster data processing and more efficient use of resources. This distributed architecture enables real-time decision-making and supports applications that require low latency and high availability.