OpenSearch multi-tenancy allows multiple users to share a cluster, and still keep their data isolated.

Understanding OpenSearch Multi-tenancy

Published November 2023

One intriguing feature of OpenSearch is its native support of multi-tenancy. But what exactly is multi-tenancy, and why is it so important? Let’s dive in.

What is OpenSearch Multi-tenancy?

Multitenancy is the ability of a single instance of software to serve many users (tenants). Each tenant operates in a dedicated, isolated environment. This isolation ensures that data, configurations, and customizations are separate from other tenants.

OpenSearch multi-tenancy allows multiple users (or teams) to share a cluster, and still keep their data isolated.

In large organizations each department might need its own search and analytics capabilities. Without multi-tenancy, a separate OpenSearch cluster must be set up for each department.

With multi-tenancy, each department functions as a separate tenant on a single OpenSearch cluster. This arrangement optimizes resource use, streamlines management, and simplifies scaling.

Why is Multi-tenancy Important?

Multi-tenancy is important for cost efficiency, simplifying OpenSearch management, scalability, and data security.

Cost Efficiency. Running separate instances for different teams or projects can be costly. Multi-tenancy allows for optimal resource use and reduces infrastructure costs.

Simplified Management. Managing a single multi-tenant cluster is easier than managing many isolated clusters. Updates, patches, and maintenance are centralized.

Scalability. As your organization grows, so do your data needs. Scaling is simpler with multi-tenancy because you’re scaling a single cluster, instead of many clusters.

Data Security. Data isolation ensures that one tenant cannot access another tenant’s data. This is crucial for maintaining data privacy and compliance.

Comparing Multi-tenancy in OpenSearch with Elasticsearch, Solr, and Other Databases

Before the fork that led to OpenSearch, Elasticsearch was the primary platform for search and analytics. Elasticsearch does support multi-tenancy. However, with the transition to a Server Side Public License (SSPL), there have been concerns about its future openness and community-driven development. OpenSearch, being fully open source, offers a more community-centric approach. This licensing ensures that multi-tenancy and other features continue to evolve based on user needs.

Check out our article OpenSearch vs. Elasticsearch for a comprehensive comparison.

Apache Solr does not natively support multi-tenancy in the same way OpenSearch or Elasticsearch does. While you can achieve a form of multi-tenancy using separate collections or cores, it’s not as integrated as in OpenSearch. This can lead to increased management overhead and complexity.

Relational databases (e.g. MySQL or PostgreSQL) don’t offer multi-tenancy in the same sense as search platforms. You can still achieve data isolation using separate schemas or databases. But, the concept of multi-tenancy in relational databases is less comprehensive. OpenSearch multitenancy encompasses configurations, plugins, and customizations along with the data.

Drawbacks of Multi-tenancy

It is important to weigh the benefits of multi-tenancy against its drawbacks.

Complexity. Multi-tenancy creates more complex OpenSearch clusters. Experienced OpenSearch engineers are best able to manage this added complexity.

Security Concerns. While multi-tenancy is designed to keep each tenant’s data isolated, there’s always a risk. If there’s a vulnerability in the system, then it could expose data from many tenants.

Resource Contention. All tenants share the same resources (CPU, memory, storage, etc.). If one tenant consumes a disproportionate amount of resources, then it can impact the performance for other tenants. This is sometimes referred to as the “noisy neighbor” problem.

Customization Limitations. There’s a limit to how much you can customize the individual tenants. This can be a drawback for tenants with very specific needs that fall outside the standard offerings.

Maintenance Challenges. Updates or changes to the system can impact all tenants. If an update introduces a bug or an issue, then it can affect every tenant on the system. This makes testing and quality assurance crucial. Check out our post on testing environments for OpenSearch for more information.

Data Backup and Recovery. Backing up data in a multitenant environment can be more complex. This is especially true if tenants require separate backup schedules or policies. Similarly, ensuring data recovery without affecting other tenants can be challenging.

Compliance Issues. Regulations for some industries prohibit storing data in a shared environment. This makes multitenancy unsuitable for those situations.

Limited Scalability. Multitenancy can be more resource-efficient initially. But there might be a point where adding more tenants to the system leads to diminishing returns in performance. At this point, scaling out might require significant architectural changes.

Shared Failures. If there’s a system-wide issue, it can impact all tenants. This contrasts with isolated environments where an issue might only affect one organization or user.

Benefits of Multi-tenancy for OpenSearch

OpenSearch multi-tenancy is beneficial for optimizing search and analytics. It offers an ideal blend of resource optimization, data security, and scalability.

At Dattell, we’ve helped many companies harness the power of multitenancy. Check out our managed OpenSearch service. We offer the most secure, stable, and customized managed OpenSearch service.

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Dattell - Kafka & Elasticsearch Support

Benefit from the experience of our Kafka, Pulsar, Elasticsearch, and OpenSearch expert services to help your team deploy and maintain high-performance platforms that scale. We support Kafka, Elasticsearch, and OpenSearch both on-prem and in the cloud, whether on stand alone clusters or running within Kubernetes. We’ve saved our clients $100M+ over the past six years. Without our guidance companies tend to overspend on hardware or purchase unnecessary licenses. We typically save clients multiples more money than our fees cost in addition to building, optimizing, and supporting fault-tolerant, highly available architectures.