Use Cases
See how teams use StreamHouse to power real-time applications, reduce costs, and eliminate operational complexity.
Real-Time Analytics
From events to insights in milliseconds
Replace complex Kafka → Flink → ClickHouse pipelines with integrated SQL stream processing. Compute aggregations, detect patterns, and power dashboards in real-time.
- 50% cost reduction vs. traditional pipelines
- Sub-second latency for aggregations
- SQL-based transformations
- Direct Grafana integration
Product Analytics
Track user behavior, compute session metrics, and detect engagement patterns in real-time across millions of events.
Log Aggregation
Store logs at S3 prices, not logging prices
Aggregate logs from across your infrastructure at a fraction of cloud logging costs. Store indefinitely in S3 with intelligent indexing for fast search.
- $0.023/GB vs. $0.50/GB cloud logging
- Infinite retention without cost explosion
- Structured log processing with SQL
- Integration with existing log shippers
Centralized Logging
Collect logs from Kubernetes pods, Lambda functions, and EC2 instances into a unified, searchable data lake.
ML Feature Pipelines
Real-time features without the infrastructure
Compute ML features in real-time with SQL. Stream to feature stores or directly to S3 for training pipelines. No separate feature engineering infrastructure.
- Real-time feature computation
- Direct S3 output for training
- Windowed aggregations for time-series features
- Feature versioning and backfill support
Fraud Detection Features
Compute transaction velocity, device fingerprints, and behavioral anomaly scores in real-time for ML models.
Change Data Capture
Sync databases without the complexity
Capture database changes and replicate to downstream systems. Built-in transformations mean fewer moving parts and easier debugging.
- Database change streaming
- Schema evolution handling
- Transformation without Debezium + Flink
- Multi-destination replication
Order Sync
Stream order changes from PostgreSQL to Elasticsearch for search and to a data warehouse for analytics.
Event-Driven Microservices
Decouple services with reliable messaging
Build loosely coupled microservices with guaranteed message delivery. Event sourcing, CQRS, and saga patterns made simple.
- At-least-once delivery guarantees
- Consumer group coordination
- Dead letter queue support
- Event replay for debugging
Order Processing
Orchestrate inventory, payment, shipping, and notification services with reliable event-driven communication.
IoT Telemetry
Handle millions of device messages
Ingest, process, and store telemetry data from IoT devices at scale. Real-time alerting and long-term storage in one platform.
- High-throughput ingestion (50K+ msg/sec)
- Real-time anomaly detection
- Long-term storage at S3 prices
- Time-series aggregations with SQL
Fleet Monitoring
Track vehicle location, engine diagnostics, and driver behavior for thousands of vehicles in real-time.
Trusted by engineering teams
See what teams are saying about StreamHouse.
“We cut our streaming infrastructure costs by 75% and eliminated two full-time positions worth of Kafka maintenance.”
Sarah Chen
VP Engineering, DataFlow Inc
“The SQL processing alone saved us from deploying a separate Flink cluster. Our pipeline went from 5 services to 1.”
Marcus Johnson
Staff Engineer, AnalyticsCo
“Finally, a streaming platform that doesn't require a dedicated team to operate. It just works.”
Emily Zhang
CTO, StartupXYZ