---
title: Approximate percentiles | Tiger Data Docs
description: Construct and run approximate percentage queries using uddsketch or tdigest
---

This walkthrough uses a `response_times` table to show approximate percentiles end to end. TimescaleDB implements them with bounded-memory sketches instead of sorting every value, which keeps latency predictable on large datasets and continuous aggregates.

By default, TimescaleDB Toolkit uses `uddsketch`, but you can also choose `tdigest`. For algorithm trade-offs, see [advanced aggregation methods](/docs/build/data-management/hyperfunctions/percentile-approx/advanced-agg/index.md).

## Run an approximate percentage query

In this procedure, we use an example table called `response_times` that contains information about how long a server takes to respond to API calls.

1. **Create a continuous aggregate for daily aggregates**

   ```
   CREATE MATERIALIZED VIEW response_times_daily
   WITH (timescaledb.continuous)
   AS SELECT
     time_bucket('1 day'::interval, ts) as bucket,
     percentile_agg(response_time_ms)
   FROM response_times
   GROUP BY 1;
   ```

2. **Query the ninety-fifth percentile over the last 30 days**

   Re-aggregate the aggregate to get the last 30 days:

   ```
   SELECT approx_percentile(0.95, percentile_agg) as threshold
   FROM response_times_daily
   WHERE bucket >= time_bucket('1 day'::interval, now() - '30 days'::interval);
   ```

3. **Create an alert**

   ```
   WITH t as (SELECT approx_percentile(0.95, percentile_agg(percentile_agg)) as threshold
   FROM response_times_daily
   WHERE bucket >= time_bucket('1 day'::interval, now() - '30 days'::interval))


   SELECT count(*)
   FROM response_times
   WHERE ts > now()- '1 minute'::interval
   AND response_time_ms > (SELECT threshold FROM t);
   ```

For more information about percentile approximation API calls, see the [hyperfunction API documentation](/docs/reference/toolkit/percentile-approximation/uddsketch/percentile_agg/index.md).