Serverless Built for bursty, high-fan-out traffic.
A serverless backbone for real-time analytics
Feed dashboards, feature stores and anomaly detection from a Kafka cluster that scales with your traffic in under a minute and never bills you extra for the fan-out. Nothing to size before a launch, a backfill or a reporting peak.
- Capacity in <60s
- No fee per consumer
- No maintenance windows
- Free migration
Example monthly invoice
10 MiB/s in · 20 MiB/s out · 7-day retention- Data in10 MiB/s × $25
- $250
- Data out20 MiB/s × $25
- $500
- Storage7 days of writes ≈ 6.3 TB × $20
- $126
- Public internet trafficData sent and read, any volume
- $0
Illustrative example at list price — a single dashboard and warehouse consumer reading the same stream. Add a third or fourth consumer and only the data-out volume changes, never a per-consumer fee. Model your own workload.
- GB/sSustained throughput per cluster
- <60 sTo scale for a traffic spike
- 99.9%Contractual uptime SLA
- $0Extra fees for public internet traffic
What "real-time" means here
Built for scale, not a latency promise
We optimize for throughput headroom and elasticity — sustained gigabytes per second per cluster, capacity changes in under a minute — not for shaving milliseconds off a single write.
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Elasticity, not a sizing exercise
Nothing to size and no capacity to reserve before a launch, a backfill or a seasonal spike in reporting load — and a capacity change lands in under a minute.
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Consumer-lag visibility, not a latency SLA
Every cluster ships with throughput and consumer-lag dashboards so you can see exactly how far behind a consumer is — a more useful signal for analytics pipelines than a single-write latency number.
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No maintenance windows
Upgrades and scaling happen with no downtime, so a scheduled maintenance job never quietly delays a dashboard refresh.
Built for analytics traffic
What changes when analytics traffic spikes
Bursty, high-fan-out workloads are the normal case for analytics pipelines, not the edge case.
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Scale in seconds, not a maintenance window
Capacity changes land in under a minute, so a reporting peak or a backfill job never needs a capacity plan filed a month ahead.
Higher limits on request
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Fan out without a second bandwidth bill
A dashboard, a warehouse load and an alerting job can all read the same topic as independent consumer groups, without adding a per-consumer public internet fee.
One data-out rate, any number of readers
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Works with the tools you already use
Kafka-compatible with your existing stream-processing and warehouse tooling — moving over is a connection-string change, not a rewrite.
Free migration
Reliability & performance
The numbers we sign up to
With service credits attached when we miss them.
- 99.9%Uptime SLAUnder 44 minutes a month, with service credits
- ZeroMaintenance windowsUpgrades and scaling with no downtime for you
- 11 9sData durabilityEvery write on durable, verified storage
- <60 sCapacity changesScale up for a peak, down the same evening
Works with your stack
Keep the tools your team already knows
ntail plugs into the engines, warehouses and dashboards you run today.
- Apache SparkBatch & structured streaming
- Apache FlinkStateful stream processing
- SnowflakeCloud data warehouse
- ClickHouseReal-time analytics
Not seeing yours? Tell us what you run — the list is longer than the grid.
FAQ
Common questions about analytics pipelines
Can ntail handle traffic spikes from real-time reporting jobs?
Yes. Capacity changes land in under a minute with no maintenance window, and you're billed per started hour for what you actually use — not for headroom reserved ahead of a launch or a reporting peak.
What's the write latency?
We publish throughput and elasticity figures rather than a latency number — sustained gigabytes per second per cluster, and capacity changes in under a minute. If your pipeline has a specific latency requirement, talk to us about it directly.
Can multiple consumers read the same stream?
Yes. A dashboard, a warehouse load and an alerting job can all read the same topic independently, as separate consumer groups, and reading data out is never billed extra for public internet traffic regardless of how many destinations there are.
Does it integrate with our existing analytics stack?
Yes. ntail works with the streaming clients, connectors and analytics tools your team already uses — Spark, Flink, Snowflake, Databricks, ClickHouse and the rest. Moving over is a connection-string change and a credential, not a rewrite.
Can I start on the free plan?
Yes. Build the pipeline on a free Kafka cluster: a real managed cluster at $0 a month, with no card and no time limit, 200 KiB/s in and 400 KiB/s out measured after compression, which is about 1,000 typical JSON events a second read back by two consumers. Upgrade to the paid plan when the pipeline outgrows it and your clusters stay where they are.
Give your analytics pipeline room to grow
Start on the free plan today — no card, no time limit — or model your throughput, fan-out and retention to see what it costs once you outgrow it.