TCO of meeting resiliency, backup, and DR

Summary

• The total cost of ownership (TCO) of resiliency, backup, and disaster recovery (DR) is driven by four things: your recovery targets (RTO and RPO), the cost of storing and replicating data to a second region, the compute you keep on standby, and the engineering effort to build and maintain it all.
• There is no single price: cost scales with how aggressive your recovery targets are. Keeping data replicated and rebuilding on failover is the lowest-cost approach; running full workloads in two regions at once (active/active) is the highest.
• For most DR approaches, data storage and cross-region replication are the largest cost component, while the increase in compute (DBU) spend stays marginal because the secondary region is not actively running workloads until a failover.
• Databricks Managed Disaster Recovery lowers the TCO of resilience by operating the DR infrastructure for you, with managed replication of Unity Catalog managed tables, external table metadata, and workspace objects, plus stable URLs, so teams avoid building and maintaining a complex do-it-yourself solution.
• Because the lakehouse stores data in open formats on your cloud object storage and Unity Catalog governs it centrally, resilience extends data you already hold, and system tables give you the cost visibility to monitor and attribute DR spend.

TCO of meeting resiliency, backup, and DR

The total cost of ownership of resiliency, backup, and disaster recovery is the full cost of being able to keep running, and to recover your data and workloads, when a region or service goes down. It is not a single number: it depends on how quickly you need to recover (your recovery time objective, or RTO), how much data you can afford to lose (your recovery point objective, or RPO), and the architecture you choose to meet those targets. Tighter targets cost more.
The main cost drivers are storing and replicating data to a secondary region, any compute you keep on standby there, and the engineering effort to build, test, and maintain the solution. Databricks provides both the architectural guidance to right-size those choices and a managed offering that removes much of the do-it-yourself cost.

Why Databricks for resiliency, backup, and DR

• Match cost to your recovery targets. DR approaches range from lower-cost patterns that keep data replicated and rebuild the environment on failover, up to active/active setups that run workloads in two regions at once. Choosing the approach that fits your RTO and RPO lets you balance cost against how fast you need to recover.
• Pay mostly for data, not idle compute. For approaches other than active/active, data storage and cross-region replication are typically the largest cost component; the increase in compute (DBU) spend stays marginal because the secondary region is not actively running workloads until a failover.
• Reduce do-it-yourself effort with Managed Disaster Recovery. Databricks Managed Disaster Recovery operates the DR infrastructure for you, with managed replication of Unity Catalog managed tables, external table metadata, and workspace objects, plus stable URLs, so platform teams do not have to build and maintain a complex custom solution.
• Build on data you already hold. The lakehouse stores data in open formats on your cloud object storage, and Unity Catalog governs it centrally, so backup and replication extend the storage you already use rather than adding a separate system.
• See and attribute the spend. Databricks system tables and unified cost views let you monitor consumption and understand the full cost of resilience across both Databricks and cloud infrastructure.
• Prove it works. Regular failover exercises validate that recovery procedures work and stay within target, reducing the risk, and cost, of a failed recovery during a real outage.

Getting started

• Plan your strategy: Disaster recovery in the Databricks documentation, starting with understanding your business needs (RTO and RPO).
• Test your recovery: Reliability best practices: test recovery procedures.
• See a customer example: How Databricks Managed Disaster Recovery helps Capital One achieve lakehouse resilience.
• Understand full cost: Getting the full picture: unifying Databricks and cloud infrastructure costs.

FAQs

What drives the cost of disaster recovery on Databricks?

The biggest drivers are storing and replicating data to a secondary region, any standby compute you keep there, and the engineering effort to build, test, and maintain the solution. Your RTO and RPO targets determine how much of each you need.

What is the lowest-cost DR approach?

Keeping your data replicated to a secondary region and rebuilding the environment on failover is the lowest-cost pattern; running full workloads in two regions simultaneously (active/active) carries the highest cost.

How does Databricks reduce the TCO of resilience?

Databricks Managed Disaster Recovery operates the DR infrastructure and handles replication of Unity Catalog managed tables, metadata, and workspace objects, so teams avoid the cost and complexity of building and maintaining a do-it-yourself solution.

How often should DR be tested?

Databricks recommends running regular failover exercises to confirm recovery procedures work and stay within your recovery targets.