Real time data feeds
Consume market data, IoT signals, and social events the instant they happen.
A price changes on an exchange.
A sensor fires in a warehouse.
A tweet goes viral.
Your system needs all three signals.
Three APIs. Three formats. Three problems.
One goes down. You miss the signal.
npayload unifies every source into one feed.
Your systems react the instant it happens.
See how it flows
Instant signal delivery
Events arrive the moment they happen. No polling intervals. No batch delays. Your systems react in real time.
Any source, one interface
Market feeds, IoT sensors, social APIs, news streams. All arrive through the same npayload channels.
Guaranteed ordering
Streams and message groups ensure your systems process signals in the exact sequence they occurred.
Replay from any point
Missed something? Seek to any offset and replay events from where you need them.
How it works
Connect to your data sources
Market feeds, IoT sensors, social APIs. One integration point for everything that moves your business.
Events arrive instantly
No polling intervals. Events are pushed to your systems the moment they happen.
Your systems react in real time
Algorithms, dashboards, and workflows consume events with guaranteed ordering and delivery.
Real Time Data Feeds: Before and After
Without npayload
- Market data, IoT signals, and social events arrive through separate, incompatible pipelines
- Missing events during a brief outage means gaps in your data that are expensive to fill
- Scaling to handle bursts of data requires manual provisioning days in advance
- Consumers that fall behind have no way to catch up without replaying the entire feed
- No schema validation means bad data enters your pipeline and corrupts downstream systems
With npayload
- Unified streaming infrastructure for market data, IoT, social feeds, and any other source
- Durable streams with consumer offsets mean no data gaps, even during outages
- Auto scaling cells absorb traffic bursts without pre provisioning
- Consumer offsets let slow consumers catch up from exactly where they left off
- Event catalogue validates every message before delivery, keeping your pipeline clean
npayload vs Building Real Time Feeds Yourself
| Feature | npayload | Build it yourself |
|---|---|---|
| Stream processing | Durable streams with consumer offsets and replay | Kafka clusters or custom stream infrastructure |
| Data validation | Schema validation at ingestion via event catalogue | Validation logic scattered across consumers |
| Backfill | Seek to any offset and replay from that point | Custom backfill pipelines per data source |
| Multi source | Adapters normalize data from any source into unified streams | Custom connector per data source |
| Scaling | Auto scaling cells handle bursts automatically | Partition management and broker scaling |
| Compaction | Compacted channels provide latest value per key | Log compaction configuration and monitoring |