Real-time Analytics
Turn streaming data into instant insights with scalable real-time analytics solutions
Core Capabilities
Stream Processing
High-throughput real-time data processing at scale
- Event stream processing
- Complex event processing
- Real-time aggregations
- Stateful computations
Real-time Analytics
Instant insights from streaming data sources
- Live dashboards
- Real-time metrics
- Anomaly detection
- Predictive analytics
Event Processing
Intelligent event-driven architectures
- Event routing
- Pattern matching
- Event correlation
- Real-time decisions
Our Approach
1
Design
Architecture design for real-time processing
- Requirements analysis
- Technology selection
- Architecture design
- Performance modeling
2
Development
Implementation of real-time pipelines
- Stream processing
- Event handling
- State management
- Pipeline development
3
Deployment
Production deployment and scaling
- Infrastructure setup
- Pipeline deployment
- Performance tuning
- Monitoring setup
4
Operations
Ongoing management and optimization
- Performance monitoring
- Scalability management
- Issue resolution
- Continuous improvement
Technology Stack
Messaging:
Apache Kafka
Processing:
Apache Flink
Analytics:
Apache Spark
Cache:
Redis
Storage:
TimescaleDB
Visualization:
Grafana
Monitoring:
Prometheus
Search:
Elasticsearch
Success Stories
Leading IoT Provider
IoT & Manufacturing
Challenge
Process and analyze real-time data from 1M+ IoT sensors for predictive maintenance
Solution
Implemented distributed real-time processing platform with ML-powered analytics
Results
- 100K events/second processing
- < 50ms latency
- 45% maintenance cost reduction
- 99.99% platform uptime
Global E-commerce Platform
Retail
Challenge
Real-time inventory and pricing updates across multiple marketplaces
Solution
Built event-driven architecture for real-time inventory synchronization
Results
- Real-time price optimization
- 30% reduction in overselling
- 2x faster market response
- 100% data consistency