Modern distributed systems require increasingly secure, low-latency, and high-throughput transaction handling—particularly in healthcare, finance, and real-time scheduling.
Conventional blockchain architectures often lack the performance efficiency needed for such reactive environments.
To address this, a high-throughput reactive microservice framework extending BigchainDB is proposed for decentralized and scalable transaction processing.
- Problem 1: CPU and Queue Congestion Under Load
- Problem 2: Complexity of Blockchain Integration
- Problem 3: Handling Real-Time Data Updates
- 1. Prerequisites & System Setup
- 2. Build & Push Docker Images
- 3. Kubernetes Deployment
- 4. Testing Blockchain & API Connectivity
- 5. ReactiveChainDB API Endpoints
- 6. Real-Time WebSocket Streaming
- 7. Kubernetes Maintenance Commands
- 8. Log Monitoring
- 9. Final Deployment Overview
- License
During high-traffic simulations (1,000 requests in batches), the system hit a bottleneck in Batch 5, where a temporary slowdown caused the maximum response time to spike to 4. 37 seconds due to CPU and queue congestion.
We implemented a Parallel Backpressure-Handling Algorithm using Sinks. Many.
- The reactive buffer was dynamically reconfigured and resized at runtime to adapt to fluctuating workloads.
- Leveraging Non-Blocking I/O combined with reactive backpressure allowed the system to recover quickly.
- After the temporary surge, response times stabilized back to the 30–70 ms range.
Hyperledger Fabric was initially explored due to its modular design.
However, its complexity conflicted with the goal of creating a lightweight, reactive integration.
We pivoted to BigchainDB, which offered a lighter and more reactive-friendly framework.
To further mitigate slowness from direct blockchain queries, we developed a hybrid caching layer using Redis:
- Instead of querying BigchainDB on each read,
- We cached transaction URLs in Redis mapped to User IDs
- Allowing instant lookups and minimal blockchain load.
Traditional REST API polling was too slow and inefficient for low-latency environments such as healthcare, finance, and real-time systems.
This caused delays in propagating fresh data to clients.
We built a Redis Watcher Service + WebSockets architecture.
- The service watches for specific User ID updates in the Redis cache
- On change, it triggers an immediate request to BigchainDB
- The updated data is pushed instantly to the client via WebSocket
- Completely eliminating the need for repeated polling
Modern decentralized microservices must support secure, reactive, and high-throughput transaction flows.
Blockchain-backed systems like BigchainDB, Tendermint, Redis, and Reactive Java make this possible — but deployment requires a reliable, scalable orchestration layer.
To achieve this, we deploy the entire ReactiveChainDB stack into a Kubernetes-based distributed environment for real-time, fault-tolerant transaction processing.
sudo apt install docker.io -ycurl -sfL https://get. k3s.io | sh -kubectl get nodes
### Pull Images from Docker Hub
docker pull namanoncode/bigchaindb:latest
docker pull namanoncode/reactivechaindbv1:latest
docker pull tendermint/tendermint:v0.31.5
docker pull redis:7
kubectl create namespace reactivechaindbEnsure YAML files exist in your repository.
kubectl apply -f namespace.yaml
kubectl apply -f mongodb. yaml
kubectl apply -f bigchaindb.yaml
kubectl apply -f redis.yaml
kubectl apply -f reactivechaindb. yamlkubectl -n reactivechaindb get pods -wkubectl exec -it -n reactivechaindb deploy/bigchaindb -- bashcurl http://localhost:26657/statuscurl http://localhost:9984/api/v1Creates a new BigchainDB blockchain transaction.
Endpoint:
POST http://localhost:8080/appointments/create3
Example:
curl -X POST "http://localhost:8080/appointments/create3" \
-H "Content-Type: application/json" \
-d '{"userId": 648263, "details": "Checkup"}'Adds a new version transaction to BigchainDB.
Endpoint:
PUT http://localhost:8080/appointments/update? userId=31323
Example:
curl -X PUT "http://localhost:8080/appointments/update? userId=31323" \
-H "Content-Type: application/json" \
-d '{"updated": true}'ReactiveChainDB uses a Redis Watcher + WebSocket system to deliver instant appointment updates.
Clients subscribe via:
ws://<server-ip>:8080/ws/appointments? userId=<id>
Example:
ws://139.84. 169.197:8080/ws/appointments? userId=648263
/appointments/create3/appointments/update?userId=<id>
No polling. Pure real-time updates.
kubectl rollout restart deploy/reactivechaindb -n reactivechaindbkubectl delete pod --all -n reactivechaindbkubectl delete ns reactivechaindbkubectl logs -n reactivechaindb deploy/bigchaindb -fkubectl logs -n reactivechaindb deploy/bigchaindb -c tendermint -fkubectl logs -n reactivechaindb deploy/reactivechaindb -fYour full decentralized microservice stack is now operational:
| Component | Description |
|---|---|
| BigchainDB Ledger | Immutable blockchain storage |
| Tendermint Consensus Engine | Byzantine fault-tolerant consensus |
| MongoDB Document Store | Persistent data layer |
| Redis Hybrid Cache | High-speed caching & pub/sub |
| ReactiveChainDB Spring Boot API | Reactive REST API layer |
| Real-Time WebSocket Streaming | Live event broadcasting |
✅ All running inside Kubernetes, fully scalable and production-ready.
Proprietary Freeware License
This software is provided free of charge for personal, educational, or commercial use. However, the following restrictions apply:
- ❌ No reverse engineering, decompilation, or source code derivation
- ❌ No modification or derivative works
- ❌ No redistribution for a fee
- ✅ Must be used in its original, unmodified form
© 2026 Naman Jain — All rights reserved.
See the full [LICENSE](LICENSE. md) for complete terms.