Extracellular Chooses TDengine for Scalable, Future-Proof Bioprocess Data Management

Extracellular, a pioneering biotech company based in the UK, specializes in cell-cultivated product manufacturing by optimizing bioprocesses for scalable and efficient cell growth. Their mission is to streamline and accelerate the development of cell-based processes by providing cutting-edge biomanufacturing expertise, helping companies transition from R&D to large-scale production.

The Challenge: Finding the Right Database for Bioprocess Data

Bioreactors used in bioprocessing generate vast amounts of time-series data, including temperature, pH levels, dissolved oxygen, and nutrient consumption. This data must be ingested in real time, analyzed for process optimization, and stored efficiently for historical insights and regulatory compliance.

Extracellular needed a scalable and cost-effective solution that could:

• Ensure real-time dashboards and analytics for operators and scientists.

• Handle high-frequency data ingestion using MQTT for seamless equipment integration.

• Maintain low-latency access to historical data for machine learning and process optimization.

• Scale efficiently as the company expanded operations from lab to full-scale production.

• Run both in the cloud and locally without vendor lock-in.

Why TDengine? Benchmarking Against Other Time-Series Databases

Before selecting a database, Extracellular benchmarked TDengine against two other popular time-series databases (TSDB), evaluating all solutions across critical industrial requirements:

For Extracellular, TDengine’s edge–cloud synchronization was the biggest advantage. Unlike other TSDBs, where edge–cloud replication can be unreliable, TDengine supports it natively, ensuring seamless data continuity across their lab and manufacturing sites.

Additionally, while TDengine’s open-source offering is robust and feature-rich, other TSDBs’ open-source versions lack essential functionality for industrial use. In one case, the evaluated open-source TSDB did not support clustering, meaning it could not scale across multiple nodes, and queries were limited to only the most recent 72 hours of data, making it unsuitable for long-term analytics.

“TDengine has been a game-changer for us. Its features designed for industrial use cases, such as native replication and HA, as well as stream processing, have far exceeded our expectations. Of course, the performance is also brilliant, capable of running well on the edge and in the cloud. The support from the TDengine team has been exceptional, making our transition seamless and ensuring our success from day one.“

— Alex Tolenaar, Technical Specialist, Extracellular

TDengine’s Built-in Industrial Capabilities

As an industrial biotech company, Extracellular required a time-series database that could natively support:

• ✅ Edge-cloud synchronization: ensuring continuous operations and real-time synchronization

• ✅ High availability (HA): critical for maintaining uptime in manufacturing.

• ✅ Tiered storage: automatically archiving long-term data to cost-effective cloud storage

These were must-haves for their operations, and TDengine delivered them out of the box, while other TSDBs required third-party solutions for similar functionality.

Deployment Roadmap: Cloud to Edge to High Availability

Extracellular structured its TDengine deployment in three key phases to optimize data flow, reliability, and cost efficiency.

Phase 1: TDengine Cloud for Centralized Data Management

• Initial deployment of TDengine Cloud to consolidate data from lab and manufacturing sites

• Seamless edge–cloud synchronization to ensure all sites store data centrally

• Real-time dashboarding and historical data analytics using Grafana

Phase 2: Edge Deployment for Real-Time Decision-Making

• Installing TDengine on-premises at lab and plant sites to store and process data locally

• Ensuring continuous operations even if internet connectivity is lost

• Edge buffering before syncing with TDengine Cloud, reducing latency for local analytics

Phase 3: High Availability for Reliability and Data Integrity

• Deploying TDengine in HA mode to prevent data loss and ensure system redundancy

• Automated replication across multiple nodes for fault tolerance

• Tiered storage for long-term retention on cloud-based object storage (S3, GCS, B2, etc.)

Results and Future Plans

By choosing TDengine over other TSDBs, Extracellular has ensured a scalable, cost-effective, and high-performance data infrastructure tailored for industrial use. Key benefits include:

• Seamless edge-to-cloud integration with zero third-party dependencies

• Lower latency for real-time decision-making and historical analysis

• Full control over data with self-hosted deployment options — unlike other TSDBs’ cloud lock-in

• Significant cost savings by avoiding other TSDBs’ high pricing for HA and cloud services.

Looking ahead, Extracellular plans to expand TDengine’s role in advanced data science workflows, AI-driven process optimization, and multi-site data synchronization for full-scale bioprocessing.

Conclusion

Extracellular’s decision to implement TDengine over other time-series databases highlights the importance of edge–cloud synchronization, high availability, and tiered storage in industrial applications. As bioprocessing scales up, a robust, open-source, and cost-effective time-series database is essential for success.

With TDengine, Extracellular is future-proofing its operations — ensuring seamless data collection, real-time insights, and long-term scalability in one unified platform.