A system for a multi-tenant API framework in scalable cloud-based database solutions

Abstract

A system for a multi-tenant API framework in scalable cloud-based database solutions, which includes the following: an API layer module that enables access to database services for multiple tenants; a tenant management module configured to handle tenant authentication, authorization, and role-based access control; a data partitioning module for partitioning tenant-specific data into isolated database structures; a resource allocation module for the dynamic allocation of computing resources to individual tenants based on usage patterns; a security module configured to protect tenant data through encryption and secure data transmission; A monitoring and analysis module for real-time monitoring of tenant activities and system performance.

Description

The present invention relates to cloud computing and database management systems, and more particularly to a tenant-enabled API framework for efficiently managing scalable cloud-based database solutions.With the rapid advancement of cloud computing and database technologies, companies increasingly employ cloud-based solutions for the storage, management, and processing of data. The tenant capability of cloud databases allows multiple users (tenants) to share the same infrastructure while maintaining logical isolation, thereby reducing cost and improving scalability. Companies such as SaaS (Software as a Service) providers, company platforms, and big data applications rely on tenant-enabled architectures to efficiently serve multiple customers. However, existing approaches to managing tenant databases have several limitations that impact performance, security, and scalability.Conventional tenant-enabled database management systems may be roughly divided into four approaches. The first approach, the single-tenant architecture, provides each tenant with its own database instance. This, while providing strong isolation and security, is resource intensive and costly and often results in inefficient use of the computing resources. The second approach, common databases with tenant-specific tables, manages a common database, but assigns each tenant its own tables. This results in a high complexity of the scheme and problems in maintenance, which in turn results in performance degradations as the number of tenants increases. The third approach, common databases with row-level security, stores data for all tenants in the same tables and uses filtering based on the tenant ID. This method involves considerable security risks, since misconfigureds can lead to unauthorized access and data leaks. Hybrid approaches eventually attempt to balance security, cost, and scalability by combining elements of the above methods.The conventional tenant-enabled database management systems have several disadvantages. One of the major constraints is the lack of scalability, as performance bottleneck arises as the number of tenants grows, which affects the execution times of queries. Most conventional systems rely on static load balancing that cannot be matched to real-time load variations. Moreover, management of schemas in a tenant-enabled environment is complex because tenant-specific table structures result in schema drift, which complicates upgrades and optimizations. Security and compliance are also a major problem, especially in row-level security mechanisms that are prone to misconfigureds, increasing the risk of data violations. Moreover, compliance with standards such as GDPR, HIPAA, and SOC 2 is difficult to enforce in shared environments.Another critical disadvantage is inefficient resource utilization because fixed resource allocation models result in either an over or underutilization of computing power and memory. Scaling operations often require manual interventions, which leads to delays and inefficiencies in resource allocation. Moreover, conventional systems lack a dynamic API framework for tenant management. Existing APIs are static and non-configurable, making it difficult for the tenants to adapt the interactions with the system. The lack of automated API provisioning forces designers to create individual integrations, which increases development time and complexity.To overcome these limitations, a tenant-enabled API framework is needed that provides scalable performance without security penalty. An ideal solution would dynamically provide APIs for each tenant while implementing secure authentication mechanisms. It should include smart load balancing techniques to optimize execution of queries and allow automatic scaling based on real-time workload analysis. Moreover, robust safety measures must be enforced to ensure compliance with data protection regulations. The present invention provides an advanced multi-tenant API framework that can be seamlessly integrated into scalable cloud-based database solutions and improves performance, security, and resource efficiency.To solve this problem, the present invention provides a system for a tenant-enabled API framework in scalable cloud-based database solutions.The system for a tenant-enabled API framework in scalable cloud-based database solutions may design an API framework that enables dynamic resource allocation and automatic scaling based on real-time workload analysis.The system for a tenant-enabled API framework in scalable cloud-based database solutions may implement smart load balancing techniques that efficiently distribute database queries, reduce latencies, and improve response times.The system for a tenant-enabled API framework in scalable cloud-based database solutions may provide robust data isolation by implementing advanced authentication and access control mechanisms that prevent unauthorized access between tenants.The system for a tenant-enabled API framework in scalable cloud-based database solutions may provide row, schema, and instance level security policies that conform to industry rules such as GDPR, HIPAA, and SOC 2.The system for a tenant-enabled API framework in scalable cloud-based database solutions may develop a dynamic API provisioning system that enables each tenant to obtain a customized API interface based on its specific requirements.The system for a tenant-enabled API framework in scalable cloud-based database solutions may facilitate on-demand API generation and versioning, thus ensuring seamless updates and backward compatibility.The system for a tenant-enabled API framework in scalable cloud-based database solutions may introduce a schema management framework that prevents schema drift and simplifies tenant-specific table changes.The system for a tenant-enabled API framework in scalable cloud-based database solutions may include query optimization techniques that improve database performance while maintaining scalability.The system for a tenant-enabled API framework in scalable cloud-based database solutions may provide compatibility with the key cloud service providers such as AWS, Microsoft Azure, and Google Cloud, thus allowing easy introduction and provisioning.The system for tenant-enabled API frameworks in scalable cloud-based database solutions may support hybrid cloud and on-premium environments and offers flexibility to companies with different infrastructure requirements.The system for a tenant-enabled API framework in scalable cloud-based database solutions may enable automated monitoring of compliance with privacy and security policies, thus ensuring compliance with legal requirements.The system for a tenant-enabled API framework in scalable cloud-based database solutions may implement audit logging and anomaly detection mechanisms to track API interactions and prevent unauthorized data access.In one embodiment, a system for a tenant-enabled API framework is provided in scalable cloud-based database solutions. The system utilizes advanced data partitioning, dynamic resource allocation, and robust security mechanisms to support scalability, performance, and isolation of tenant data. The system comprises an API layer for flexible communication between tenants and the cloud database, which supports common protocols such as RESTful and GraphQL. A tenant management unit ensures secure authentication, authorization and role-based access control for each tenant. The data partitioning engine isolates the data of the individual tenants using partitioning strategies such as domain or hash based partitioning to maintain data protection and optimize performance. The resource allocation modules dynamically allocate computing resources (e.g., CPU, memory, memory) based on the tenant's specific usage patterns, thus ensuring optimal performance at different workloads. The security layer employs encryption, tokenization, and other protection mechanisms to protect tenants' data during both transmission and idle. The monitoring and analysis unit keeps track of API usage, system performance, and tenants' activities in real-time, and provides insight into resource usage, bottleneck, and potential issues, enabling efficient management and proactive optimization.The invention is explained again below with reference to the figure. The following shows: FIG. 1 : shows a system for a tenant-enabled API framework in scalable cloud-based database solutions.FIG. 1 illustrates a system for a tenant-enabled API framework in scalable cloud-based database solutions. The system includes an API layer module, a rental management module, a data partitioning module, a resource allocation module, a security module, and a monitoring and analysis module, each of which performs specific functions to provide efficient, secure, and scalable operation of the cloud-based tenant database solution. The module of the API layer acts as an interface through which multiple tenants interact with the cloud-based database services. It supports communication protocols such as RESTful and GraphQL and allows the tenants to access their data flexibly and securely. This module forwards tenant requests to the corresponding data partitions and includes functions such as tenant-specific rate limiting to control API usage to prevent congestion of the service and ensure fair resource distribution. The tenant management module is responsible for managing tenant authentication, authorization, and role-based access control (RBAC). This module facilitates creation, modification and deletion of tenant accounts and ensures that each tenant's access to the system is securely managed based on predefined roles and permissions. Moreover, this module provides a self-service portal that allows tenants to manage their account settings, configure access controls, and monitor their use. The data partitioning module ensures that tenants' data remains isolated and secured by partitioning into separate database structures such as schemas, tables, or collections. This module uses partitioning strategies such as range-based, hash-based, or composite partitioning, depending on the data characteristics of the individual tenants. It also supports horizontal scaling, i.e., distribution of data among multiple physical or virtual machines, to meet the growing requirements of tenants without compromising data integrity or performance. The resource allocation module dynamically allocates computational resources such as CPU, memory, and storage space to each tenant based on their usage patterns. By monitoring the real-time requirement, the module adjusts the resources as needed, thus ensuring optimum performance at different workloads. The module also includes machine learning based models that predict trends in resource demand based on historical usage data, thus optimizing resource allocation for both high and low demand tenants. The security module provides comprehensive protection for tenant data by applying encryption techniques to both idle and transmission data. This module also uses tokenization to protect sensitive data and to ensure compliance with data protection regulations. It also includes an audit trail function that records access protocols, rental actions, and system changes, thus providing detailed history for security and compliance audits. Finally, the monitoring and analysis module collects and analyzes data about API usage, system performance, and tenant activities. It generates real-time insights and performance metrics that assist administrators in monitoring system state and resource usage. This module is also capable of generating automatic alerts based on predefined conditions, such as resource congestion, performance degradation, or unusual activities, enabling proactive management and optimization of the cloud-based database system.List of reference characters100 System

Claims

A system for a multi-tenant API framework in scalable cloud-based database solutions, comprising: an API layer module that enables access to database services for multiple tenants; a tenant management module configured to handle tenant authentication, authorization, and role-based access control; a data partitioning module for partitioning tenant-specific data into isolated database structures; a resource allocation module for dynamically allocating computing resources to individual tenants based on usage patterns; a security module configured to protect tenant data through encryption and secure data transmission; a monitoring and analysis module for real-time monitoring tenant activities and system performance.The system of claim 1, wherein the API layer module supports multiple communication protocols including RESTful and GraphQL and allows rentalers to interact with the cloud-based database via flexible interfaces.The system of claim 1, wherein the tenant management module enables dynamic creation, modification, and deletion of tenant accounts and ensures that each tenant's data access is controlled by a role-based access control (RBAC).The system of claim 1, wherein the data partitioning module partitions data into logical units including, but not limited to, schemes, tables, or collections, thereby ensuring that the data remains isolated and secure for each tenant.The system of claim 1, wherein the resource allocation module dynamically allocates resources such as CPU, memory, and storage space based on the usage patterns of the individual rentalers, thereby ensuring optimal performance at different workloads.The system of claim 1, wherein the security module employs encryption techniques including data-at-residue encryption, data-in-transit encryption, and tokenization to protect rental data from unauthorized access and to ensure compliance with privacy regulations.The system of claim 1, wherein the monitoring and analysis module collects and analyzes data about API usage, database performance, and tenant activity, thereby providing real-time insights into system state and resource usage to administrators.The system of claim 1, wherein the data partitioning module applies one or more partitioning strategies including range-based, hash-based, and composite partitioning based on the data characteristics of each tenant.The system of claim 1, wherein the resource allocation module dynamically adjusts the resources in real-time based on preconfigured thresholds to ensure that high demand rentals do not affect system performance for other rentals.The system of claim 1, wherein the API layer module includes a tenant-specific rate limiting function that enables individual tenants to limit the frequency of requests, thereby preventing congestion of the service and ensuring fair resource distribution.

Images