Use Cases

The most popular use cases for PipelineDB are realtime reporting dashboards and realtime monitoring systems. But PipelineDB can be used for any realtime analytics applications where you know the queries you want to run in advance and can express your queries in SQL.

Realtime Reporting Dashboards

Easily build realtime reporting dashboards for internal or customer-facing use. Because summary analytic data is pre-computed by PipelineDB’s continuous query engine before it is stored, any time users refresh their PipelineDB-powered dashboard their analytics will be realtime up to the second.

-- Calculate the number of unique users seen per url referrer each day using only a constant amount of space per day
CREATE CONTINUOUS VIEW uniques AS
SELECT
day(arrival_timestamp),
referrer::text,
COUNT(DISTINCT user_id::integer)
FROM users_stream GROUP BY day, referrer;

-- How many ad impressions have we served in the last five minutes?
CREATE CONTINUOUS VIEW imps WITH (max_age = '5 minutes') AS
SELECT COUNT(*) FROM imps_stream

-- Join conversions on any prior clicks that may have caused them
CREATE CONTINUOUS VIEW click_throughs AS
SELECT
day(arrival_timestamp),
campaign_id, COUNT(*), COUNT(DISTINCT user_id)
FROM conversions JOIN clicks USING(user_id, campaign_id)
WHERE conversions.timestamp > clicks.timestamp
GROUP BY day, campaign_id;

More examples can be found here.

Realtime Monitoring Systems

Monitor systems in realtime using continuous SQL queries and take action when certain criteria are met. Sliding window queries enable you to easily define custom time windows for systems monitoring using regular SQL and power realtime monitoring applications or dashboards.

-- What are the 90th, 95th, and 99th percentiles of my server’s request latency?
CREATE CONTINUOUS VIEW latency AS
SELECT
percentile_cont(array[90, 95, 99])
WITHIN GROUP (ORDER BY latency::integer)
FROM latency_stream;

-- Heavy hitters: how much traffic are each of the top-10 IP addresses making requests to my server generating?
CREATE CONTINUOUS VIEW heavy_hitters AS
SELECT
day(arrival_timestamp),
fss_agg(ip, 10, response_size)
FROM requests_stream GROUP BY day;

Swag for Stories

Are you using PipelineDB in production and open to sharing your use case with the world? Fill out the form below and we’ll send you a PipelineDB hoodie if your company is selected for a case study, which we’ll publish on our website and send out to the PipelineDB community.