The world is becoming increasingly unpredictable.
Service outages, network failures, data center fires, and temporary cloud region shutdowns—events often labeled as Black Swans, which are hard to foresee, unlikely to occur, yet highly disruptive when they do—are now part of everyday business risk.
The real issue is this: every time a Black Swan strikes, your core enterprise data can be brought to a halt by a single point of failure.
Data Cannot Stop: The Foundation of Business Continuity
By 2025, enterprise data protection strategies have started to shift rapidly.
In the past, the primary question was, “Which DBMS best fits our workload?”
Today, a far more strategic question is coming to the forefront:
“What is our database replication and disaster recovery (DR) strategy?”
Recent incidents—such as outages at major cloud service providers like Azure and AWS, the Kakao data center fire, and fires at the National Information Resources Service—have made one thing clear: enterprises can no longer treat data failures as rare exceptions.
A single outage can result in billions of won in direct losses, along with long-term damage to customer trust.
In this context, DB replication has become a critical strategy for mitigating risk.
To prepare for such events, organizations must minimize their RTO (Recovery Time Objective).
RTO is not just the time required to restore a database; it covers the entire time until end users can actually use the service again. If the database at the foundation of the system stack is not recovered, RTO will inevitably be delayed.
In other words, DB recovery is the starting point of full system recovery.
And to support this, organizations must drive RPO (Recovery Point Objective)—the allowable amount of data loss—down to zero.
Simply having backups is no longer enough. To approach RTO = 0, the database must be replicated in real time, not just periodically backed up.
All modern business runs on data. When the database stops, the business stops.
Enterprises therefore need more than just “stored” data—they need a DBMS replication architecture that enables immediate recovery.
From Backup to Real-Time Replication: How DR Has Evolved
Traditional data protection strategies were largely built around backup and restore, often offloading backups to tape and storing them externally. This approach has inherent limitations:
- Recovery takes time.
- There is always a risk of data loss between the last backup and the point of failure.
To address these limitations, two main approaches emerged:
- Storage-based replication – Replicating data at the storage level between storage systems
- DB-level data synchronization – Sending DBMS transaction logs to maintain consistent data between systems (commonly used for HA, High Availability)
Today, enterprises typically look at these two options when implementing real-time replication and automated failover.
However, due to some practical constraints, DB-level data synchronization–based HA configurations are increasingly preferred.
Limitations of Storage-Based Replication
Key drawbacks of storage-based replication include:
- Real-time synchronization is often an add-on feature from the storage vendor and is frequently priced higher than DB-level HA options.
- Instead of synchronizing only log files like an HA setup, storage replication copies all DB-related files (Data, Redo, Archive, Flashback, Control, Temp, etc.), which adds significant overhead.
- Even small changes in data can trigger replication at large block sizes, leading to inefficiency.
- Because DB volumes need to be remounted on the target side, failover times tend to be longer.
By contrast, DB-level data synchronization works with the database already mounted and simply replicates log records. The benefits are clear:
- Failover can occur almost immediately in the event of a failure.
- Recovery times are significantly reduced.
For these reasons, TmaxTibero recommends DB-level data synchronization–based HA configurations when designing DR architectures.
Originally, HA was designed to provide high availability within a single data center.
Today, the same approach has evolved to support RPO = 0 even across geographically separated data centers.
Active Data Replicator (ADR): A More Advanced DB Replication Approach
More recently, architectures where the DBMS itself manages real-time replication and automated failover—an Active–Standby DB replication model—have gained attention.
Tibero’s Active Data Replicator (ADR) is a representative example of this evolution in DB replication.
Key characteristics include:
- An independent disk–based cluster architecture where each database instance is accessed by exactly one server for read/write operations
- In the event of a failure, the Standby node immediately assumes the Primary role, minimizing service downtime
- Automated log synchronization and transaction management to ensure data consistency
Because replication and role switching are handled directly by the DBMS, this architectural model delivers:
- Much shorter RTO (faster recovery) compared to external backup or storage-based systems
- An RPO close to zero, resulting in virtually no data loss
Going forward, enterprise data strategies must move away from a mindset focused purely on “storage” and instead prioritize continuity.
The DBMS Evaluation Criteria Are Changing: From Performance to Resilience
Historically, organizations evaluated DBMSs primarily based on:
- Features
- Performance
- Licensing and operating cost
Now, new factors are taking precedence:
- Robust disaster recovery frameworks
- Maturity and performance of synchronization mechanisms
- Level of automation in replication and failover
This shift is more than a technology preference—it is a strategic move to reduce business risk.
Only systems that support resilient DB replication and enable rapid response to unexpected failures can truly protect data reliability and service continuity.
DB Replication Must Be Architected for Scalability
Enterprise IT environments are more complex than ever:
- On-premises systems and multiple clouds coexist
- Commercial and open-source DBMSs are mixed
- Various multiple platforms are integrated into a single landscape
Given this complexity, DB replication can no longer be thought of as a single, uniform pattern. What enterprises need is a scalable DR strategy.
In the following parts of this series, we will explore three key approaches to DB replication:
- Same DBMS DR Replication
– Stable replication topologies and implementation practices within a single DBMS platform - Different DBMS DR Replication
– Data synchronization and replication techniques across different DBMS platforms - N:1 and 1:N DR DB Architectures
– Strategies for consolidating multiple DBs into a single DR target, or distributing DR roles across multiple systems by business domain
As DB replication evolves, both its scope and technical depth are expanding.
The more widely enterprise data is distributed across platforms and environments, the more important it becomes to integrate everything into one unified resilience framework.
Black Swans Are Inevitable. Large-Scale Damage Is Not.
Black Swans can appear at any time, in any part of your infrastructure.
They cannot be completely eliminated—but their impact can be significantly contained.
That preparation begins with a database replication strategy.
DB replication is not just about preventing outages.
It is about having the ability to recover immediately when outages do occur.
Many organizations still view DB replication as a “nice-to-have contingency.” That perspective is now outdated.
In a world where data is the business, DBMS replication is:
- Part of the core operating architecture, not an emergency plan
- A baseline requirement for service reliability and customer trust
In this era of unpredictable Black Swans, only organizations with a recoverable database can claim to have true data resilience.
