Compare Paragon vs. Peaka

Create production-ready integrations in just minutes instead of taking months. Paragon is a low-code platform designed to simplify the process of building product integrations, enabling you to provide your customers with desired features more swiftly. Concentrate on refining your product rather than on the complexities of writing integrations. With Paragon, you can utilize our visual workflow editor to establish production-ready integrations that connect seamlessly to your application in a matter of minutes. This allows you to dedicate your efforts to developing your core product instead of spending excessive time piecing together various services or crafting integration code. Enhance developer productivity and roll out new features effortlessly without the need for manual coding of integrations. The collaboration between product and engineering teams is facilitated by Paragon’s intuitive visual workflow editor. Additionally, Paragon automatically scales to ensure rapid performance while eliminating the need for you to manage your own infrastructure. Effortlessly connect with your customers' applications, as they expect your product to integrate smoothly with their other cloud services. Paragon simplifies the creation of user-facing integrations, allowing you to embed them directly within your product and enhance the user experience. By doing so, you can not only meet customer expectations but also foster stronger relationships with them.

Unify all your data sources, encompassing both relational and NoSQL databases, SaaS applications, and APIs, allowing you to query them as if they were a single data entity instantly. Process data at its source without delay, enabling you to query, cache, and merge information from various origins seamlessly. Utilize webhooks to bring in real-time streaming data from platforms like Kafka and Segment into the Peaka BI Table, moving away from the traditional nightly batch ingestion in favor of immediate data accessibility. Approach every data source as though it were a relational database, transforming any API into a table that can be integrated and joined with your other datasets. Employ familiar SQL syntax to execute queries in NoSQL environments, allowing you to access data from both SQL and NoSQL databases using the same skill set. Consolidate your data to query and refine it into new sets, which you can then expose through APIs to support other applications and systems. Streamline your data stack setup without becoming overwhelmed by scripts and logs, and remove the complexities associated with building, managing, and maintaining ETL pipelines. This approach not only enhances efficiency but also empowers teams to focus on deriving insights rather than being bogged down by technical hurdles.