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Meta search engine development: where the difficulty actually is

A meta search engine queries many suppliers at once and returns one ranked answer in real time. It looks like a product problem and is a latency problem. We have run one at 300 million queries a day; this page explains what that took.

Book a scoping callTravel software development

The engine behind this page

300,000,000
queries a dayReal-time price and availabilityMetasearch case study
60%
lower response timeAgainst the engine it replacedMetasearch case study
80%
lower infrastructure costHotel metasearch platformMetasearch case study
For
Travel and comparison platforms whose search slows at peak or costs too much to run.
Starting point
A scoping call and a written ballpark; an existing engine starts with measurement.
Pricing
Time and materials against the written ballpark you receive after the scoping call.
Cost drivers
The number of suppliers, the traffic you expect and how fresh prices have to be.
What it covers

The four problems a metasearch engine has to solve

  • Supplier aggregation

    Querying many suppliers in parallel and returning before the slowest one answers, which means deciding what a partial answer looks like.

  • Caching strategy

    Deciding per data type how stale an answer may be. Some prices tolerate minutes, some seconds, some nothing. This decision, not hardware, is what decides perceived speed.

  • Ranking and filtering

    Sorting and filtering results without a second round trip per interaction, which pushes the data into memory close to the request.

  • Failure behavior

    What a customer sees when a supplier times out or answers nonsense, designed rather than discovered.

  • They're very skilled technically and are also able to see the bigger picture. Stratoflow can actually think about solutions, not just the technical task at hand, which they've been assigned.
    Arnd Jan PrauseChief Operating Officer, musQueteer
Where the work goes

Most of the engineering is caching, timeouts and partial results

Prices live in systems you do not control and change constantly, so a design that waits for every supplier is only as fast as the slowest one. The work goes into deciding how stale each kind of data may be, how long to wait for each supplier and what to show when one does not answer.

That is how we rebuilt a UK hotel metasearch engine. It now serves 300 million queries a day at 60 percent lower response time and 80 percent lower infrastructure cost, mostly from removing repeated work rather than buying faster machines.

If your supplier count and traffic are modest, a standard platform will do. Talk to us when the numbers are large enough that the architecture decides your speed and your costs.

Delivery process

How metasearch engine development with Stratoflow works

Each phase is agreed with you first, and results are measured against your current engine.

  1. Scope the search

    We begin with a scoping call on your suppliers, your traffic and how fresh prices must be, and you receive a written ballpark.

  2. Measure or design

    In the second phase, we measure the current engine or design a new one: supplier calls, caching, timeouts and failure behavior.

  3. Build in increments

    Then we build or rework the engine in increments, testing each against real supplier responses and load tests at the traffic you expect.

  4. Release and compare

    Finally, we release it, compare speed and running cost against the baseline, and hand over the code and the operating guidance.

Case studies

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Metasearch guides from our engineers

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Written by , Co-founder and CTO, Stratoflow. Published . Updated .

Next step

Discuss your metasearch engine

Bring your supplier count, peak traffic and how fresh prices must be. We will show you where the time and money go.

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