---
title: "What's the Best API for Event Data?"
category: "comparisons"
url: https://keirolabs.cloud/blog/best-api-for-event-data
---

Event data has a free answer and it is Ticketmaster's Discovery API, as long as your agents stay under 5,000 calls a day. For every event Ticketmaster does not sell, a search or scraping API covers the gap. This post prices seven real routes into event data, from free official APIs to enterprise contracts, using each vendor's own documentation.

The searches that led here ask the same thing in a dozen ways: which API offers best event data, which one aggregates the leading event databases, which one wins on analytics. The honest answer is that "event data" is two markets wearing one name. Ticketed inventory has official APIs. Everything else, free community events, conferences, meetups, local festivals, is coverage work that no official API does completely. Pick by workload, then check the rate limits, because those limits decide whether your agent survives its first good month.

## What Is the Best API for Event Data?

For ticketed events, Ticketmaster's Discovery API is the best deal in the market. It is free, it covers 230,000+ events across the US, Canada, Mexico, Australia, New Zealand, the UK, Ireland and other European countries, and it returns structured JSON with price ranges, onsale dates and canceled or postponed status. The catch is the quota: a default of 5,000 API calls per day and 5 requests per second, with higher limits granted case by case after Ticketmaster verifies your application ([Ticketmaster developer docs](https://developer.ticketmaster.com/products-and-docs/apis/getting-started/)).

For everything with a start time that nobody sells a ticket to, no official API covers the ground. That is where search APIs and scrapers come in. Here is the field, priced per 1,000 requests or events as of September 23, 2026:

| Provider | What it is | Coverage | Price | Hard limit | Access |
|---|---|---|---|---|---|
| Ticketmaster Discovery API | Official ticketing inventory | 230,000+ events, 8+ countries | Free | 5,000 calls/day, 5 req/s | Self-serve key; application for more |
| SerpApi (Google Events) | Scraped Google event listings | Whatever Google shows | From $25.00/1k, free 250/mo | 20% of monthly volume per hour | Self-serve |
| Apify event scrapers | Per-site scraping actors | Eventbrite, Ticketmaster, more | $1.00-$2.00 per 1,000 events | Actor run time | Self-serve, pay per event |
| Keirolabs | Search API over the open web | Any event page on the web | /search/fast 1 credit ($0.80/1k on Startup), /search/content 3 credits | 30 to 1,000 req/min by plan | Self-serve, no card |
| Eventbrite API | Your own Eventbrite events | Your organisation only | Free | ~2,000 calls/hour | OAuth token |
| SeatGeek | Marketplace events | SeatGeek marketplace | No published rate card | Not published | Request-gated portal |
| PredictHQ | Aggregated demand intelligence | 100M+ events, 19 categories | Custom contract | Not published | Sales-led |

The two-market split explains most of the confusion in this category. Reviews that rank "event APIs" against each other are usually comparing a ticketing inventory feed against a demand-forecasting platform against a SERP scraper, which is like comparing a cash register to a newspaper. Each is correct for a different job.

So the direct answer, by job:

- Selling or displaying tickets: Ticketmaster Discovery API, free, official, authoritative.
- Discovering events across many sources: a search API (Keirolabs, SerpApi) or scrapers (Apify), because no official API aggregates the open web's event pages.
- Forecasting demand: PredictHQ, if your budget survives the contract.
- Managing events you host on Eventbrite: Eventbrite's own API, free.

> One number decides most builds here: 5,000. That is Ticketmaster's daily call ceiling, and it is lower than most products assume.

## Leading Event Databases in One API

The phrase in our search logs that gets the most impressions, 237 a month for "leading event databases in one api", is really a question about aggregation. Can one API hand you what Ticketmaster, Eventbrite, SeatGeek, venue calendars and city listings all know?

The honest answer: only two things come close, and neither is an event API in the classic sense.

PredictHQ aggregates hardest. Its platform tracks over 100 million events across 19 categories, from concerts and sports to school holidays and observances, and adds modeled attributes like predicted attendance and predicted spend ([PredictHQ pricing](https://www.predicthq.com/pricing)). That is a genuine "leading databases in one API" product. It is also a contract: no public rate card, no self-serve tier, sales-led onboarding. You will not find a price on the page because the page does not have one.

Google Events, accessed through SerpApi or similar SERP scrapers, is the cheap approximation of aggregation. Google already merges listings from Ticketmaster, Eventbrite, venue sites and local promoters into one event result, and SerpApi returns that merged listing as JSON for one search credit. At $25.00 per 1,000 searches on the entry plan ([SerpApi pricing](https://serpapi.com/pricing)), it is the fastest way to prototype cross-source event search. The ceiling is Google's: you get what Google's event carousel shows, with Google's gaps, and every result is one credit whether it holds 30 events or zero.

A search API takes the third path. Keirolabs' /search endpoints query the open web directly, so the "database" is whatever venue sites, city calendars, ticketing pages and aggregators have published. /search/fast costs 1 credit per request; /search/content costs 3 and returns full page markdown, which matters when your agent needs the speaker list or the schedule hiding in the page body. On the $100 Startup plan that fast search is $0.80 per 1,000 requests, and content pulls are $2.40 per 1,000 ([Keiro pricing](https://keirolabs.cloud/pricing)). The trade is yours to manage: no vendor's schema, so your code does the normalizing.

One API that quietly does aggregate five sources: Ticketmaster itself. The Discovery API draws from Ticketmaster, Universe, FrontGate Tickets, TicketWeb and Ticketmaster Resale with one key ([Discovery API docs](https://developer.ticketmaster.com/products-and-docs/apis/discovery-api/v2/)). If your definition of "leading event databases" is "the Live Nation ecosystem", you already have your aggregator.

What nobody in this list does: hand you SeatGeek, Eventbrite and Ticketmaster merged under one schema. SeatGeek's classic REST API (api.seatgeek.com/2/events with client credentials) still answers for its own marketplace, but new access runs through a request-gated developer portal with no published pricing ([SeatGeek developer portal](https://portal.seatgeek.com/)). Eventbrite retired public event search from its API entirely. The consolidation everyone feared on the search-API side has quietly happened in events too.

- PredictHQ: true aggregation, 100M+ events, 19 categories. Cons: custom pricing, sales-led, overkill for lookup workloads.
- Google Events via SerpApi: merged cross-source listings, structured JSON. Cons: one credit per search regardless of result count, Google's coverage is Google's ceiling.
- Keirolabs: whole-web reach, clean JSON or full page markdown, cheapest per 1,000. Cons: you build the schema and the dedupe.
- Ticketmaster: five ticketing platforms behind one key. Cons: ticketing only, 5,000 calls/day.

> Every aggregator's real product is deduplication, and nobody publishes their error rate on it.

## Which API Offers Best Event Data

"Best data" needs a definition before it needs a vendor. In practice we grade event sources on five things: field completeness, freshness, entity resolution, timezone correctness, and whether the output is clean JSON or HTML you must parse. Here is how the field actually scores.

Field completeness. Ticketmaster returns the richest structured record in the market: names, images, venue with coordinates, priceRanges, onsale and offsale timestamps, and status flags for canceled, postponed or rescheduled events. PredictHQ layers modeled fields on top (predicted attendance, predicted spend, impact patterns). Scraped and search-based sources give you whatever the page had, which varies by source and sometimes omits price: Apify's Eventbrite actors note that only promoted listings carry a price field, about 1 in 25 results measured in September 2026, so organic rows come back with the price field empty.

Freshness splits the market cleanly. Official APIs are authoritative for their own inventory: when a show cancels, Ticketmaster's status field flips, and that is the record your users should see. Scraped SERP data and search indexes inherit the source page's freshness, which on small venue sites can lag by days. An agent that shows a canceled event as onsale does not get forgiven, so freshness is not a nice-to-have. Coverage is a landing page claim; freshness is what your users notice.

Entity resolution is where every source quietly struggles. The same show appears as "Taylor Swift | The Eras Tour" on Ticketmaster, "Taylor Swift: The Eras Tour" on Google, and "Taylor Swift - The Eras Tour" on a venue page, with the venue sometimes named "MetLife Stadium" and sometimes "MetLife Stadium, East Rutherford, NJ". No event API in this list resolves that for you across sources. PredictHQ does entity work inside its own database, which is part of what the contract pays for. If you merge sources yourself, budget real engineering time for the dedupe layer: match on normalized title plus venue identifier plus start-time bucket, not on title alone.

Timezones are the bug that never dies. Event pages publish local times; your database wants UTC; the venue sits in a DST-observing timezone. Official APIs usually return both the local time and the timezone, which is correct. Scrapers frequently return a rendered string like "7:30 PM" with no zone attached, and your agent guesses. A wrong event time is worse than a missing event, so this single field should drive your source choice more than price does.

LLM-readiness, since many readers here are building agents: Ticketmaster and PredictHQ return native JSON an LLM can consume directly. SerpApi returns structured JSON parsed from Google. Keiro's /search/content returns page markdown, which is what a model reads natively, and its /answer endpoint returns cited natural-language answers at 5 credits. Raw scraping returns HTML, which costs you a parsing layer that breaks whenever the source redesigns.

Worked example, one event through five sources. Take a Saturday show at MetLife Stadium. Ticketmaster's API returns the full record in one call, including $60 to $250 price ranges and an onsale date. SerpApi's Google Events engine returns the listing Google shows, one credit, with date, venue and ticket links. Keiro /search/fast finds the venue's own event page in 1 credit, and /search/content pulls the whole page as markdown in 3, including the support act and the bag policy nobody's API carries. PredictHQ returns the event with a predicted attendance figure your forecasting model can use. SeatGeek would return its marketplace view, if your access request went through. Five sources, five schemas, one event, and only one of them is authoritative for whether it sold out this morning.

## Best Event Data API

Match the API to the workload. Here is each option with its actual trade-offs.

- **Ticketmaster Discovery API.** Pros: free; 230,000+ events across 8+ countries; the best structured fields in the category, including priceRanges, onsale dates and status; rate-limit headers (Rate-Limit-Available, Rate-Limit-Reset) your code can read; covers five ticketing platforms under one key. Cons: 5,000 calls/day and 5 req/s by default; higher limits need an application and verification; Ticketmaster inventory only; nothing outside its country list; not a discovery layer for events Ticketmaster does not sell.
- **SerpApi Google Events.** Pros: cross-source listings Google has already merged; structured JSON with dates, venues and ticket links; free plan at 250 searches/month; cached and errored searches do not burn credits. Cons: entry pricing is $25.00 per 1,000 searches, falling to about $9.17 at the top self-serve plan; throughput is capped at 20% of monthly volume per hour; you inherit Google's coverage decisions; one search bills one credit whether the result set is full or empty.
- **Apify event scrapers.** Pros: pay per event, roughly $1.00 to $2.00 per 1,000 events on the Eventbrite actors; no subscription; JSON/CSV export; scheduled runs keep data fresh. Cons: per-site, so you maintain an actor per source; scraping breaks when layouts change; price fields often missing (only promoted listings carry them); scraping public pages sits on the wrong side of some sites' terms.
- **Keirolabs.** Pros: cheapest structured retrieval in the field at /search/lite $0.25 per 1,000 headline and $0.08 per 1,000 on the $100 Startup plan; /search/fast at 1 credit ($0.80/1k on Startup); /search/content returns full page markdown at 3 credits ($2.40/1k on Startup) for schedule pages and venue sites; free tier of 1,250 credits monthly, no card; 1,000 req/min on Startup. Cons: not a curated event database, so your code normalizes results; no ticketing-level inventory state (availability lives on the seller's page); one-time credit packs bill lite at 0.5 credit, so the monthly plan is the cheap path.
- **Eventbrite API.** Pros: free; about 2,000 calls/hour; full lifecycle for events you host, from creation through orders and attendee check-ins; webhooks instead of polling. Cons: public event search is retired, so it cannot discover anyone else's events; it is an organizer's API, not a discovery API; OAuth setup and scoping take real care.
- **SeatGeek API.** Pros: the classic REST API is documented and free with client credentials; strong marketplace data with seat maps. Cons: new access runs through a request-gated portal with no published rate card or pricing, so you are applying, not signing up; coverage is SeatGeek's marketplace.
- **PredictHQ.** Pros: 100M+ events across 19 categories; predicted attendance and spend attributes; a Forecasts API built for demand modeling; entity work and labeling done for you. Cons: custom contract pricing with no public rate card; sales-led, so prototyping means talking to someone; overkill if your app just shows a city's weekend.

Three picks cover most readers. A consumer app showing concerts and games: Ticketmaster first, SerpApi or Keiro alongside it for what Ticketmaster lacks. An agent doing open-ended event research: Keiro /search/content at $2.40 per 1,000 on Startup, with /agentic at 20 credits for the multi-step queries. A forecasting or pricing model: PredictHQ, budgeted as an enterprise line item.

> A free API with a 5,000-call daily ceiling is free until the day your product works.

## Leading Event Data API

Which of these is the "leading" event data API depends on the metric, but the pricing table below settles the part that is arithmetic. Rates checked September 23, 2026, from each vendor's own pages.

| Provider | Published rate | The catch | Source |
|---|---|---|---|
| Ticketmaster Discovery API | Free | 5,000 calls/day, 5 req/s default; more requires an application and verification; Ticketmaster-family inventory only | [Ticketmaster docs](https://developer.ticketmaster.com/products-and-docs/apis/getting-started/) |
| SerpApi Google Events | $25.00/1k entry, $15.00/1k on Developer ($75/mo, 5,000 searches), $9.17/1k at 30,000/mo | Free plan is 250 searches/month; throughput capped at 20% of monthly volume per hour; every response costs one credit even when empty | [SerpApi pricing](https://serpapi.com/pricing) |
| Apify Eventbrite scrapers | $1.00-$2.00 per 1,000 events | Price field populated only on promoted listings (about 1 in 25 results); per-site actors; platform compute on top | [rowfeed actor](https://apify.com/rowfeed/eventbrite-events-scraper), [automation-lab actor](https://apify.com/automation-lab/eventbrite-scraper) |
| Eventbrite API | Free | About 2,000 calls/hour; public event search retired; your own organisation's events only | [Eventbrite rate limits](https://www.eventbrite.com/platform/docs/rate-limits) |
| Keirolabs | /search/fast 1 credit; /search/lite 0.1 credit on plans | Free tier is 1,250 credits/month, no card; on Essential ($30/mo, 12,500 credits) fast is $2.40/1k; Pro ($50/mo) $1.33/1k; Startup ($100/mo) $0.80/1k; lite is $0.24/1k, $0.13/1k and $0.08/1k on those plans; packs bill lite at 0.5 credit | [Keiro pricing](https://keirolabs.cloud/pricing) |
| SeatGeek | No published rate card | Classic API free with client credentials, but new access is request-gated; limits and pricing not published | [SeatGeek portal](https://portal.seatgeek.com/) |
| PredictHQ | Custom contract | No self-serve tier; features gate behind plan conversations | [PredictHQ pricing](https://www.predicthq.com/pricing) |

Now the cost math that actually decides things. Lookups of event data at three volumes, per month, cheapest sensible self-serve configuration:

| Volume of event lookups | Ticketmaster Discovery | Keiro /search/fast (Startup) | SerpApi Google Events | Apify Eventbrite (per event) |
|---|---|---|---|---|
| 10,000 | $0 (fits quota) | $8.00 | $250.00 entry / $91.70 at scale rate | $10.00-$20.00 |
| 100,000 | $0 but impossible: needs 3,334 calls/day, under quota with little headroom | $80.00 | $2,500.00 entry / $917.00 at scale rate | $100.00-$200.00 |
| 1,000,000 | Impossible: 33,334 calls/day vs the 5,000 quota | $800.00 | $25,000.00 entry / $9,170.00 at scale rate | $1,000.00-$2,000.00 |

Three observations worth the read. First, Ticketmaster's free quota covers about 150,000 calls a month in theory, which is plenty for a lookup feature and nowhere near enough for a bulk pipeline; at one million monthly lookups you would need the quota to reset 200 times. Second, Keiro's Startup plan clears one million fast lookups in about 17 hours at its 1,000 req/min limit, for $800, which is the only column in the table where a million-row month is routine rather than an exception request. Third, the scraped routes (SerpApi, Apify) price per result set or per event, so their cost scales with what you find, while Keiro's scales with what you ask, and those are different curves; a city with a thin event scene costs the same to query either way, but an Apify actor bills per event row returned.

Rate limits deserve the same arithmetic as price, because they set your architecture. Ticketmaster at 5 req/s means a nightly job over 5,000 artists takes 17 minutes of wall clock, fine, but a bursty product feature that fires 500 calls in a minute will throttle and your users will see the timeout, not the API. SerpApi's 20% rule means a 1,000-search-per-month plan can only run 200 searches in any hour, so batch jobs spread across the night by design. Keiro's plan limits run 30 req/min free, 60 on Essential, 300 on Pro, 1,000 on Startup, and the batch endpoint runs many queries asynchronously at 1 credit per query. Plan the burst, not just the bill.

## Best-Rated Event Data API

"Best-rated" is the hardest claim to verify in this market, because no third party publishes an event-data leaderboard the way AIMultiple ranks search APIs or Patronus ranks financial QA. We can tell you what the search-side scoreboards show, and they matter here only as a proxy: on AIMultiple's 2026 Agentic Index, Keirolabs scored 15.2 out of 20, ahead of Brave at 14.89 and Exa at 14.39, and on FinanceBench financial QA Keiro scored 78% ([AIMultiple](https://aimultiple.com), [FinanceBench post](/financebench)). Those are retrieval benchmarks, not event benchmarks, but they test the same underlying skill your event agent needs: finding the right page and returning what it says.

For event data specifically, you are the rating agency. The harness we would build, and have built for search APIs: 100 queries across 5 cities and 3 verticals (concerts, sports, conferences), a ground-truth set built by hand from venue sites, and three checks. Recall: what fraction of the real events did each source find? Freshness: re-query 48 hours later and count how many statuses (canceled, sold out, moved) the source caught. Resolution: how many duplicate rows survive your merge? A source that wins recall by 10% but misses every cancellation is worse than the source it beat, and only your harness will catch that.

Ratings you can check without building anything: documentation quality and API explorer availability. Ticketmaster ships an API Explorer where you can fire live calls from the browser ([API explorer](https://developer.ticketmaster.com/api-explorer/)). SerpApi has a playground per engine and a free plan generous enough to test the Google Events engine properly (250 searches/month, no card). Apify shows live pricing per actor and a console that schedules runs. PredictHQ's onboarding starts with a call, which tells you what their support model is: a contract, not a dashboard.

One more signal worth weighing: how the vendor behaves when something breaks. Eventbrite retired its public search endpoint with a documentation note, which is honest but still broke discovery agents that had built on it. Google's Custom Search API closed to new customers and set a discontinuation date of January 1, 2027, which the search-API market is still digesting. An event pipeline built on one vendor is a pipeline with a single point of deprecation, and events has had more deprecations than most categories lately.

> Nobody publishes an event-data leaderboard, so your QA suite is the leaderboard.

## Is It Best Event Data API

Our Search Console logs show people typing this question without the grammar: "is it best event data api", 100 impressions a month, plus variants like "is it best-rated event data api" and "is it leading event databases in one api". The cluster of is-it queries totals several hundred monthly impressions, all asking the same thing: is there one API that is simply the best?

There is not, and the reason is structural. Official APIs are authoritative inside their fence: Ticketmaster knows Ticketmaster inventory better than any scraper ever will, and Eventbrite knows Eventbrite orders. The moment your product needs an event that lives outside the fence, and every real product does, the fence becomes the bug. Search-based and scraping approaches have the opposite shape: unlimited fence-jumping, no authority. When Ticketmaster and a promoter's page disagree about a sold-out state, one of them is wrong and your product pays for it.

So the is-it question resolves into a stack question, and the stacks are knowable:

- Ticketing app: Ticketmaster Discovery API alone, free, 5,000 calls/day, structured JSON with prices and status. No second source needed inside the fence.
- Local discovery app: Ticketmaster for ticketed inventory, plus a search API (Keiro /search/fast at $0.80/1k on Startup, or SerpApi Google Events at $9.17 to $25/1k) for everything else, plus a scraper for the one or two sources you need in bulk.
- Forecasting model: PredictHQ's contract if attendance labels matter, or a search pipeline plus your own labeling if the contract does not fit.
- Agent doing research: a search API with page content (Keiro /search/content, 3 credits, $2.40/1k on Startup) and, for the hard multi-step queries, an agentic endpoint at 20 credits per run.

Worked example: an event-feed agent for one city. Say the product is a weekend guide for Austin, refreshed daily. The build: four Keiro /search/fast queries a day, one per category (music, sports, family, arts) at 1 credit each; /search/content pulls at 3 credits each for the 30 or so promising hits; a normalize step that pins title, venue, start time, UTC offset and price range into one schema; dedupe on venue identifier plus start-time bucket; then cache each event URL and re-check only events younger than 72 hours. That lands near 94 credits a day, about 2,820 a month, which is $6.80 a month on the Essential plan ($30 buys 12,500 credits) and $2.30 on Startup. The same four queries a day on SerpApi's Google Events engine is 120 searches a month, inside the 250-search free plan for a single city, but scale to 20 cities and you are at 2,400 searches, $60.00 at entry rates or $22.00 at the scale rate. The 30 ticketed events inside that feed cost Ticketmaster 2 or 3 calls a day against its 5,000, free, and the other categories simply do not exist in that API, which is the whole argument for the stack in one sentence.

The stack's real cost is not the per-1k rates; it is the seams. Two sources means a dedupe layer, a normalization layer, and a freshness policy per source. Three means an on-call rotation for parsers. The failure modes we have actually hit in production event pipelines, in rough order of pain: a source retires an endpoint (Eventbrite search, Google Custom Search), a layout change silently empties a field, duplicate events with different venue spellings double-count a festival, DST shifts a recurring weekly event by an hour, and a sold-out state lags by a day in scraped data but is correct in official data. None of these show up in a demo. All of them show up in week three.

> One API is a decision you can revisit. One API with no cache is a decision your vendor makes for you.

If the logs are any guide, most people asking the is-it question want permission to keep it simple. Here it is: start with Ticketmaster's free key, add one search API the day you notice what it does not cover, and cache aggressively. That stack stays honest until your usage graph says otherwise.

## Top API for Event Data Analytics

Analytics is where the two markets diverge hardest, and where the phrase in our logs, "top api for event data analytics" (46 impressions a month), points at a genuinely different tool.

For demand intelligence, PredictHQ is the category and the category is PredictHQ. Its pitch, backed by numbers on its own pages: over 100 million events, 19 categories, predicted attendance and predicted event spend as attributes, and a Forecasts API that hands your model event-driven features rather than raw listings ([PredictHQ pricing](https://www.predicthq.com/pricing)). Companies in travel, hospitality and retail use it to anticipate demand spikes around events. The cost model matches the buyer: enterprise contracts, not metered self-serve. If your model's accuracy improves 2% when it knows a stadium concert doubles Friday's hotel occupancy, that contract pays for itself. If you are building a weekend-events app, it is the wrong product at the wrong price point.

For analytics on your own event data, the official APIs win on schema stability. Ticketmaster's Discovery API has kept a stable shape across versions, which matters when your dashboards join years of history. Scraped data has no such contract: a redesign can change field names mid-quarter, and your time series quietly splits in half. When official APIs beat scraping, this is the reason: not coverage, but schema stability across the years your analytics need to span.

For bulk analytical pulls, the meter matters more than the source. Keiro's batch endpoint runs many queries asynchronously at 1 credit per query, so a 10,000-query historical sweep costs $8.00 on Startup ($0.80/1k) and runs unattended; on Essential it is $24.00. SerpApi's equivalent 10,000 searches cost $250 at entry rates, and its 20%-per-hour throughput rule spreads the job across at least five hours by design. Apify's pay-per-event actors are the cheapest bulk option where they fit, $10.00 to $20.00 per 10,000 events, but they bill per row, so a sparse source with thin results still costs its scrape compute.

Analytics also changes the freshness math. A dashboard that powers staffing decisions needs status changes within the hour, which pushes you toward official feeds and webhooks (Eventbrite pushes webhooks for orders and check-ins; Ticketmaster exposes status fields you can poll within your quota). A model that trains monthly cares about history, not minutes, which makes cached and batched approaches fine and changes which price column matters.

- Demand forecasting with attendance labels: PredictHQ, contract pricing, category leader.
- Stable schema over years of history: Ticketmaster Discovery API, free within quota.
- Bulk pulls on a budget: Keiro batch at 1 credit per query ($8/1k on Startup), or Apify per-event billing where a single source dominates.
- Live dashboards with minute-level status: official feeds first, scraping only as a gap-filler.

> Forecasting models eat years of history, and no scraper can sell you 2019.

## What's the Best API for Participant Identity and Event Extraction (Emails, Attendance, Speaker Turns)?

One query in our logs, 52 impressions a month, asks something the rest of the cluster does not: what is the best API for participant identity and event extraction from emails, attendance records and speaker turns? This is a different product from everything above. The events here are meetings, calls and conferences you already have artifacts for, and the job is pulling structured people-and-events data out of prose.

No event API in this comparison does this, because it is not a lookup problem. The tooling that works is an extraction pipeline:

1. Get the artifact into text. For public pages, a speaker lineup or an agenda page, Keiro's /extract endpoint pulls a URL into clean markdown at 3 credits per request ($2.40/1k on Startup, $7.20/1k on Essential). For email threads and internal documents, your own pipeline reads them; no external API should touch that content.
2. Have the model return structured output. Keiro's /answer endpoint (5 credits per call) returns a synthesized answer with citations, which handles "who is speaking at this event, with titles and affiliations" in one call. A raw LLM call with a JSON schema does the same job when you already hold the text.
3. Resolve people, not strings. "Dave Masuto", "D. Masuto" and "dave@keirolabs.cloud" are one participant across three threads. The resolution layer is your code: canonical email as the key, name fuzzy-match as a fallback, and a manual review queue for the collisions.

The cost of that pipeline is arithmetic: extracting 1,000 event pages and answering 1,000 structured questions over them is 3,000 + 5,000 = 8,000 credits, which is $19.20 on Keiro's Essential plan ($30/mo buys 12,500 credits), $10.67 on Pro, and $6.40 on Startup. A dedicated extraction vendor would price that same job per document; Apify has scrapers for specific platforms (meeting tools, event platforms) in the same $1-to-$2-per-1,000-records class.

Two cautions from production use. Attendance is not identity: an RSVP list tells you who was invited, a check-in list tells you who came, and email threads tell you who cared enough to reply; your schema should keep those apart or your metrics will lie to you. And participant data is personal data. Emails, attendance and speaker identities are exactly the fields privacy law cares about, so the pipeline that extracts them should live inside your trust boundary, with retention you can explain. The cheapest API in this post is free precisely because Ticketmaster never sees your inbox, and the same logic runs in reverse.

> Participants live in prose, not databases, so extraction beats lookup here.

## Best Event Data API 2025

The "best event data API 2025" searches still trickle in, 2 impressions a month, and the honest answer is that most 2025-era recommendations have aged badly in twelve months. The category repriced. What changed:

- Eventbrite retired public event search from its API. A 2025 tutorial that lists Eventbrite as a discovery API now describes an organizer's back office instead.
- SeatGeek moved developer access behind a request-gated portal. The classic client-credential API still answers, but new integrations apply and wait.
- Microsoft retired the Bing Search APIs on August 11, 2025, removing a common agent fallback for event lookups.
- Google's Custom Search API closed to new customers and set discontinuation for January 1, 2027.
- PredictHQ pushed further into AI-facing products (Forecasts API, model-ready attributes), confirming its enterprise direction.

So if your shortlist came from a 2025 listicle, re-verify every row. The parts of the 2025 picture that still hold: Ticketmaster's Discovery API is still free at 5,000 calls/day, SerpApi still sells Google's event listings from $25/1k with 250 free searches a month, and Apify's community actors still scrape Eventbrite at $1 to $2 per 1,000 events.

The 2026 verdict, compressed. Ticketed inventory: Ticketmaster, free, and stop looking. Cross-source discovery: a search API, priced from $0.80/1k (Keiro /search/fast on Startup) to $25/1k (SerpApi entry), with Apify actors as the bulk lever for one dominant source. Forecasting: PredictHQ, budgeted as a contract. Participant extraction: an extraction pipeline, not an event API, at 3 to 8 credits per artifact. And whatever you pick, build the freshness check before the launch: 48 hours later, re-query, and count what changed. Every rate in this post was checked against the vendor's own pages on September 23, 2026. Prices change, quotas get renegotiated, and this market has repriced twice in twelve months; check again before you build on anyone, including us.