Migrating 100TB+ from HBase to MongoDB in Under 48 Hours
Accelerating Enterprise Data Modernization
When a MarTech company began planning the modernization of its core customer data platform, an early estimate from another consulting firm suggested that migrating 100TB of data and making the required application changes could take up to three years.
The leadership team knew that the timeline was unacceptable. Its data platform supported mission-critical retail analytics, and the business could not afford prolonged disruption or a multi-year technical transition.
“At this rate of speed we calculate it will take approximately three years to migrate your data…”
That is what the previous firm told our customer.
It did not sound like the island vacation they promised…
We did it in under 48 hours!
The Delbridge Approach
Delbridge began the engagement by developing a deep understanding of the company’s data architecture and business processes. The team worked closely with the company’s internal engineers to map out the application and data interactions and came up with a detailed data migration and application remediation plan. To further accelerate the project, parallel project workstreams were initiated to complete both the migration and application remediation at the same time, with extensive system integration testing at the end to integrate the work products from both streams.
Through this collaboration, Delbridge gained insight into the required data throughput and scope of application microservices in need of remediation. Having assessed the unique landscape of the services and infrastructure, there was a clear opportunity to leverage Adiom’s DSync migration tool. Its horizontal scale-out capability meant it could be leveraged to meet the required data throughput to accelerate the data migration, to support large-scale and complex migrations.
In summary, the overall project philosophy rested on three pillars:
Use off the tested shelf migration technology to expedite the data migration
A bottom up change only what is necessary at the application tier
Parrallel project work streams to meet the required project timelines
Delbridge activated Adiom to provide the migration and synchronization layer for the customer. Adiom supported a dedicated HBase connector that enabled data conversion into an optimized MongoDB schema.
To address the limitations of Change Data Capture (CDC) on HBase, a custom solution was built on top of Apache Kafka to enable real-time synchronization.
The Challange: Scale Meets Complexity
Our customer operates at an enormous data scale. Over more than two decades, the company built a powerful data ecosystem based on Apache HBase.
The environment contained more than 100 TB of active production data and collections exceeding 100 billion records. Data was distributed across region servers and stored as key‑value pairs within complex column families.
Additional complexity came from heterogeneous data formats, including Avro encoding and legacy analytics pipelines. Most importantly, the production systems could not tolerate extended downtime. The migration had to occur without interrupting critical business operations.
From a component perspective, the system resembled the following simplified design:
Delbridge transformed HBase replication into a Kafka-based CDC stream, enabling continuous change capture despite HBase’s limitations.
Workloads were divided by HBase region and executed in parallel, allowing the migration to scale efficiently across large production datasets.
Automatic CDC switching, resumability, and reverse sync support helped protect business continuity and reduce operational risk during cutover.
Migration Architecture
Parallel Processing
10 Worker Nodes
2M Writes / Second
The architecture used massively parallel processing where migration tasks were distributed across multiple worker nodes. Data partitions aligned with HBase regions, allowing independent segments to migrate concurrently.
The deployment used ten worker nodes with 16 CPUs and 64GB RAM each plus a coordinator node managing orchestration and monitoring. Performance benchmarks reached up to two million writes per second to the MongoDB Atlas destination cluster, enabling full migration windows between 24 and 48 hours.
Migration Reliability
HBase does not provide a native pull‑based change data capture stream. To maintain synchronization during migration, Delbridge developed a custom replication peer that streamed changes into Apache Kafka. This approach converted push‑based HBase replication into a resilient change stream pipeline that could be consumed by the migration system.
The architecture ensured no data changes were lost during the migration window while maintaining durability and resiliency.
Enterprise migrations must assume that failures will occur. Delbridge designed the migration system to support resumability, observability, and controlled throttling of workloads. Real‑time dashboards tracked migration progress, throughput, and estimated completion times.
A reverse‑synchronization capability allowed changes to flow back to the original HBase environment if rollback became necessary, providing additional operational confidence. The solution space was adapted to include DSync, which enabled bi-directional data movement until the platform was ready to consume MongoDB.
Production and Execution
One advantage of Delbridge’s high‑speed migration toolkit was the ability to conduct multiple full production rehearsal migrations. These dry runs enabled the team to test rollback scenarios, validate data integrity, and refine the go‑live playbook across development and UAT environments.
By the time production cutover occurred, the migration process had already been tested repeatedly under real‑world conditions.
The production rollout occurred across both United States and European environments in a sequence that minimized observable downtime. The US migration proceeded smoothly. However, during the European deployment, an expected but temporary Azure Kubernetes capacity issue interrupted the migration.
Thanks to the migration platform’s resiliency and documentation of the runbook (and rollback) procedure from dry runs, the team rolled back safely and maintained synchronization until the infrastructure issue was resolved, after which migration resumed successfully.
After a focused monitoring period post-deployment, the customer team was able to assume ownership of the solution. This allowed us to detach DSync, enable deprecation of HBase, MapReduce, and Avro transformers, and produce the following simplified component design:
Results
The MarTech company achieved a major transformation through this project. What had initially been expected to take three years was completed with less than 48 hours of production migration time, proving that large-scale modernization does not have to involve long timelines or prolonged disruption. Even at enterprise scale, the transition was executed with speed, precision, and confidence.
The outcome went far beyond a successful migration. The company achieved zero data loss, minimal operational disruption, and resilience in the face of an unplanned outage, all while moving to a modern MongoDB Atlas platform built to support future innovation and long-term growth. More than 100 TB of data and over 100 billion records were successfully migrated in under 48 hours through the partnership between Delbridge Solutions and Adiom.
This project is a strong example of what is possible when deep expertise is matched with the right migration architecture. It shows that even the most complex data modernization initiatives can be accelerated dramatically, helping enterprises reduce risk, shorten timelines, and move faster toward meaningful digital transformation.
Outcomes
- No customer disruption
- 50%+ shortened development lifecycle for new features
- Regional parallelization of data migration
- Reverse data synchronization
- Savings of over $30k/ year from deprecation
Whether you are modernizing legacy systems, migrating large and complex datasets, transforming data for MongoDB, or replacing outdated migration methods, Delbridge delivers a structured, scalable migration framework built to move your organization forward with speed, control, and confidence.
What do we deliver ?
Landing Data in MongoDB
1A stepwise migration roadmap
2An optimized data schema, in MongoDB
3Real-time synchronization
4Automated Validation
5Application Changes
6
Project Details
Project Stats
Our MongoDB Expertise
Fast Start
Migration foundation deployed with documented patterns and standards.Environment-ready and built to scale.
Best Suited For:
- Small budgets
- Fast turnarounds that demonstrate value
- Proving capability
- Building momentum
White Glove
Fully-managed delivery process where we deliver strategy, execution, and promotion along with app changes to support MongoDB
Best Suited For:
- Highly occupied teams
- De-risking delivery
- MongoDB novices
- Hitting deadlines