A multi-tenant application is a software architecture where a single instance of software runs on a server and serves multiple tenants. Tenants are separate entities or companies that use the same application, but their data and configurations are isolated from each other. This approach allows for resource sharing while ensuring that each tenant’s data remains private and secure.
The main principle behind multi-tenancy is to provide a cost-effective way for software providers to manage a single application for multiple users. It simplifies the deployment process and reduces the overhead of running separate instances for each customer. Organizations benefit from reduced costs and the ability to scale quickly as new tenants are added.
This is part of a series of articles about multi tenant architecture.
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In single-tenancy applications, each customer has their own independent instance of the software, including its infrastructure, database, and configurations. This model offers high levels of customization and security, as data is completely isolated. However, it comes with higher operational costs and complexity in managing multiple software instances.
Some examples of single tenant applications are applications that run on a dedicated virtual machines (VM) for each customer, and traditional enterprise software, such as ERP systems, where the software is installed on the customer’s own servers.
Multi-tenancy applications consolidate all users on a single software instance. Though this raises concerns about data privacy and resource contention, advancements in multi-tenant architectures have introduced mechanisms to securely separate tenant data and efficiently distribute resources. This architecture significantly reduces costs and simplifies updates and maintenance.
Probably the best known example of a multi-tenant application is Salesforce, which pioneered the concept of software as a service (SaaS). Salesforce allows multiple organizations to use the same application instance while keeping their data isolated. Another example is Google Workspace, a cloud service suite that provides productivity and collaboration tools.
Learn more in our detailed guide to multi tenant vs single tenant
Here are some examples of data management in different multi-tenant applications.
In a multi-tenant application using a single database with a single schema, all tenants share the same database and the same set of tables. Each table includes a tenant identifier column to distinguish rows that belong to different tenants. This approach simplifies the database architecture by maintaining only one set of tables for all users.
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This model involves a single database instance hosting multiple schemas, where each schema is dedicated to a tenant. It strikes a balance between completely isolated databases and a fully shared schema.
In this setup, each tenant has its own database, providing the highest level of data isolation and security. Each database can be independently managed and scaled according to the tenant’s specific needs.
Multi-tenancy is useful for several reasons.
Multi-tenant applications offer cost savings by pooling resources such as servers, storage, and maintenance efforts. This reduces the investment required to support multiple customers, enabling lower subscription fees. Additionally, the operational costs like upgrades, bug fixes, and security patches are spread across all tenants.
The architecture is designed to accommodate an increase in the number of tenants without a proportional increase in resources. This elastic scalability is crucial for organizations experiencing rapid growth or seasonal spikes in demand. Shared resources can be reallocated dynamically, ensuring that each tenant receives the necessary capabilities without over-provisioning.
Since there’s only one codebase and infrastructure to manage, developers can deploy updates, bug fixes, and new features more efficiently. All tenants benefit from improvements simultaneously, ensuring uniformity and reducing versioning conflicts. This model also streamlines backups and disaster recovery processes.
Multi-tenancy can also introduce several challenges.
The shared infrastructure in multi-tenant environments raises concerns about unauthorized access and data leaks among tenants. Strong isolation techniques, encryption, and access controls are critical to safeguard sensitive information. Compliance with regulations such as GDPR and HIPAA adds another layer of complexity.
Maintaining performance levels and ensuring that the activities of one tenant don’t affect others is challenging in multi-tenant architectures. Resource contention can lead to degraded service for some tenants, especially during peak usage times.
Efficiently onboarding new tenants and provisioning their environments in a multi-tenant architecture requires automated processes. Manual interventions can lead to delays and potential errors in the setup, including initial configurations, data isolation, and resource allocation.
Here are some practices that can help improve the design of a multi-tenant application.
Ensuring tenant isolation is crucial for security, privacy, and performance. Architects must design data storage and processing mechanisms that prevent tenants from accessing each other’s information. This includes database schema designs that keep tenant data separate and secure at all times.
Implementing network and application-level isolation further enhances security. Strategies such as virtual private networks (VPNs) and separate execution contexts per tenant ensure that interactions within the application remain confidential and protected from external threats.
Design choices should anticipate future growth in both the number of tenants and the volume of their data. This includes selecting scalable databases, optimizing application code, and utilizing cloud services that can dynamically adjust resources based on demand.
Frameworks and libraries that support horizontal scaling can facilitate growth without compromising performance. Effective cache strategies and data partitioning also play a role in managing large datasets efficiently.
Multi-tenant applications should offer flexibility for individual tenants. This allows tenants to tailor the application to their specific needs without affecting the core functionality or other tenants. Providing a range of configurable options through a user interface or API enables tenants to personalize aspects such as branding, workflows, and feature sets.
However, the design must balance customization capabilities with the need to maintain a manageable codebase and ensure overall application integrity. Techniques such as feature toggles and modular architecture support this flexibility.
Optimization strategies include rightsizing resources, implementing auto-scaling, and leveraging cloud services for elasticity. Monitoring usage patterns and dynamically adjusting resources prevent over-provisioning and minimize costs.
Optimizing application code and database queries can reduce resource consumption. Using efficient algorithms and data structures improves processing speed and decreases the need for computational resources.
Centralized monitoring and logging are essential for operational efficiency and troubleshooting in multi-tenant architectures. At the same time, systems should be able to log events and metrics in a way that differentiates between tenants, allowing for targeted analysis and problem resolution.
Tools and practices such as structured logging, tenant-specific dashboards, and alerting mechanisms support this differentiation. These provide insights into application performance and help identify issues at the tenant level without compromising privacy.
To assist tenants in adhering to data privacy laws such as GDPR in Europe or CCPA in California, multi-tenant applications should incorporate features that enable data handling in compliance with these laws. This includes providing tenants with the tools to manage data access, consent, and deletion requests effectively. Application developers should also implement logging mechanisms that can trace data access and modifications, which is important for auditing.
It is beneficial to include features that allow tenants to configure data storage locations according to regional legal requirements. For instance, certain regulations require data to be stored in the same country or region where it was collected. By enabling tenants to specify where their data is stored, developers can help ensure compliance with data sovereignty requirements.
In a nutshell, Frontegg’s PLG-centric and end-to-end user management platform is multi-tenant by design.
By developing the platform to the essential requirements of the B2B SaaS, we know that each tenant has its own configurations, user sets, and security settings. This is why Frontegg allows each environment to hold segregated sets of tenants, assign users to each one of them, and hold a separate configuration for each one of them in a way that doesn’t affect the neighboring tenants in any way or form.
In the complex B2B world, each customer requires fine grained control on each configuration. That requires professional products to keep pace with these requirements and develop a multi-tenant capable infrastructure from day 1. Frontegg just makes it easier.
