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Description

Store and manage relational data effortlessly in the cloud while enabling access through GraphQL and REST with a robust, open-source backend. Utilize GraphQL, REST, or Parse SDKs to handle your data needs efficiently, and enhance your applications with business logic via cloud functions. Experience improved app performance without the burden of infrastructure management, as you can create relational data models in a matter of minutes and execute intricate queries seamlessly within a truly serverless environment. Our experienced engineering team is available to support you at every phase of your journey, ensuring a smooth migration from database setup to cloud functions. We help you monitor and control costs effectively, even as your applications grow, by providing affordable and predictable pricing. The scaling process is automatic, and our guidance ensures a hassle-free experience. Design your application precisely to your specifications without the complexities of backend management, all while prioritizing data security, which has become increasingly vital in today's digital landscape.

Description

Experience serverless and interactive data querying with IBM Cloud Object Storage, enabling you to analyze your data directly at its source without the need for ETL processes, databases, or infrastructure management. IBM Cloud SQL Query leverages Apache Spark, a high-performance, open-source data processing engine designed for quick and flexible analysis, allowing SQL queries without requiring ETL or schema definitions. You can easily perform data analysis on your IBM Cloud Object Storage via our intuitive query editor and REST API. With a pay-per-query pricing model, you only incur costs for the data that is scanned, providing a cost-effective solution that allows for unlimited queries. To enhance both savings and performance, consider compressing or partitioning your data. Furthermore, IBM Cloud SQL Query ensures high availability by executing queries across compute resources located in various facilities. Supporting multiple data formats, including CSV, JSON, and Parquet, it also accommodates standard ANSI SQL for your querying needs, making it a versatile tool for data analysis. This capability empowers organizations to make data-driven decisions more efficiently than ever before.