When you upload and manage your data on GitHub that no one else can see unless you make it public, you share physical infrastructure with other users. That’s because GitHub uses multitenancy as a cost-effective and easier-to-manage alternative to assigning a separate database to each user.
However, sharing the same infrastructure becomes a security risk when all users can view each other’s data. Multitenancy addresses this issue by logically partitioning user data while allowing them to run on the same resources.
This article explores multitenancy in vector databases, its benefits, limitations, and real-world use cases.
How Does Multitenancy Work in Vector Databases?
Multitenancy is an approach where multiple tenants, i.e., users, share the same database but store their data in an isolated environment.
An isolated environment is created using unique credentials for each tenant to secure their data. As a result, each tenant can store, manage, and alter their data in their isolated environment. However, the company has the access to manage and control tenant resources and limitations.
Sample illustration of a two-tenant collection with isolated access to the same database. Image Source: Qdrant
Vector databases use indexing as a search technique that organizes vectors based on similarity. The indexing strategy impacts the tenant data partitioning. Currently, two indexing strategies are used in multitenant vector databases.
Let’s discuss both indexing strategies in multitenant vector databases:
- Shared Indexing: All tenants share the same index with unique credentials partitioning the data. This method is memory efficient. However, it requires robust security and access control mechanisms to protect tenant data.
- Per-tenant Indexing: Every tenant has a separate index in per-tenant indexing. This allows complete access control and improved search performance. However, this method is resource-intensive.
Some vector databases like Qdrant and Milvus offer multitenant architecture to allow added customization and scalability for users with both indexing strategies.
Benefits of Multitenancy in Vector Databases
Multitenancy in vector databases offers numerous benefits for companies that require isolated database instances for several users. Some of the benefits include:
1. Cost reduction
Using fewer resources for more users results in reduced infrastructure costs.
2. Scalability
Multitenancy allows need-based resource sharing. This means tenants with more storage requirements get more resources and vice versa.
3. Customization
A separate environment allows tenants to configure it based on their needs, including database schema, plugins, metrics, and dashboards. Configurations are private to tenants, and tenants can change them as their requirements change.
4. Manageability
A single database for all tenants allows centralized resource management, configuration, and monitoring instead of monitoring all tenants separately. While a company can manage all tenants in a single place, tenants have the control to manage their data within their isolated environments.
Limitations of Multitenancy in Vector Databases
Like any other architectural approach, multitenancy has some limitations. Considering these limitations is important for careful decision-making. The most common limitations include:
1. Additional Complexities
Managing multiple tenants on a single resource requires added configuration. This includes tenant onboarding, access control, user authentication, and authorization. Lack of knowledge and support could lead to unwanted outcomes like accidental data sharing or resource overhead.
To address this, careful planning and database support ensures a secure user environment.
2. Security Concerns
Malicious access, accidental misconfigurations, or vulnerabilities in underlying infrastructure can lead to shared data among tenants. As guardrails, implementing careful design, conducting regular audits, and incorporating multi-layer security measures can strengthen overall security.
3. Performance Bottlenecks
Higher usage of resources by a tenant can slow down the performance of others. Shared indexing specifically affects search performance due to runtime permission checks to match the access list. Resource management and control, regular updates, and tenant education are important to mitigate performance issues.
4. System Outage
Scheduled maintenance, hardware failure, and software bugs affect all tenants when they share a similar infrastructure. This leads to data, reputation, and financial losses. Regular risk assessment, infrastructure quality assurance, and timely backup can minimize the negative impact of system outages.
Use cases of Multitenancy
Multitanency is useful in various applications, from e-commerce recommendation systems to training large machine learning (ML) models in companies. A few of the most common use cases include:
1. Recommendation Systems
Imagine an e-commerce platform where users can sign up and save their shopping preferences. A multitenant setup will allow personalized product recommendations to each user.
On the e-commerce platform, all tenants can set their criteria, so the recommendation system sends personalized product recommendations to end users.
2. Enterprise Applications
Large software applications serving multiple employees and customers use the same database for all users. All users can upload and manage their data while protecting it from others. For instance, Dropbox and HubSpot allow all users to share the same resources but keep their data protected from each other.
3. Anomaly and Fraud Detection
Multitenancy allows the development of robust fraud detection systems while keeping individual data secure. Companies train fraud detection models on their anonymized data and send only the trained model over the centralized database. This allows them to keep their data secure while contributing to developing fraud detection systems.
For example, credit card fraud detection systems use ML for enhanced privacy and efficiency.
When to Use and When Not to Use Multitenancy
Multiple factors contribute to the decision to switch to multitenancy, including tenant performance, isolation requirements, and security concerns. Let’s discuss when and when not to use multitenancy in detail below.
When to Use Multitenancy
The following indicators make multitenancy a good fit:
- Multiple tenants need separate environments.
- Tenants can accept performance tradeoffs.
- Cost reduction is your priority.
- Centralized tenant management improves your operations.
When Not to Use Multitenancy
Limitations of multitenancy keep it from making a good fit for all situations. A multitenant vector database isn’t a good fit for you if you’ve the following requirements:
- Tenants own highly sensitive data with strict security requirements.
- A limited number of tenants with slow growth.
- Tenants require dedicated environments and can’t tolerate performance degradation.
- Limited multitenant expertise and capability to handle increasing complexity.
Multitenancy introduces additional scalability and manageability to the vector databases. If configured correctly, multitenancy saves significant costs and resources for an organization.
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