Skip to main content
Humanitix is a ticketing platform for events. This connector extracts events, orders, tickets, and organizers’ tags from the Humanitix API into Nekt for analysis.

​
Configuring Humanitix as a Source

In the Sources tab, click on the “Add source” button located on the top right of your screen. Then, select the Humanitix option from the list of connectors. Click Next and you’ll be prompted to add your access.

​
1. Add account access

You’ll need your Humanitix API key. Add your credentials:
  • API Key: Humanitix API key. Found under Account > Advanced > Public API key.
  • Start Date: The earliest record date to sync (ISO 8601 format). Records created or updated after this date will be extracted from the source.
Once you’re done, click Next.

​
2. Select streams

Choose which data streams you want to sync:
  • events
  • orders
  • tickets
  • tags
Select the streams and click Next.

​
3. Configure data streams

Customize how you want your data to appear in your catalog. Select the desired layer where the data will be placed, a folder to organize it inside the layer, a name for each table, and the type of sync.
  • Layer: choose between the existing layers on your catalog. This is where you will find your new extracted tables once the extraction runs successfully.
  • Folder: a folder can be created inside the selected layer to group all tables being created from this data source.
  • Table name: we suggest a name, but feel free to customize it. You have the option to add a prefix to all tables at once to make this process faster!
  • Sync Type: you can choose between INCREMENTAL and FULL_TABLE.
    • Incremental: every run fetches only new/updated records since the last replicated timestamp (supported for events, orders, and tickets via updatedAt).
    • Full table: every run fetches the current state of the stream. Use this for tags (replication is not incremental).
Once you are done configuring, click Next.

​
4. Configure data source

Describe your data source for easy identification within your organization, not exceeding 140 characters. To define your Trigger, consider how often you want data to be extracted from this source. Optionally, you can define some additional settings:
  • Configure Delta Log Retention and determine for how long we should store old states of this table as it gets updated. Read more about this resource here.
  • Determine when to execute an Additional Full Sync. This will complement the incremental data extractions, ensuring that your data is completely synchronized with your source every once in a while.
Once you are ready, click Next to finalize the setup.

​
5. Check your new source

You can view your new source on the Sources page. If needed, manually trigger the source extraction by clicking on the arrow button. Once executed, your data will appear in your Catalog.
For you to be able to see it on your Catalog, you need at least one successful source run.

​
Streams and Fields

Below you’ll find all available data streams from Humanitix and their corresponding fields.
Master data about events and their attributes.Key Fields:
  • _id: Unique event identifier (primary key)
  • userId, organiserId
  • currency
  • name, description, sharingDescription, slug, url
  • tagIds
  • category
  • classification.category, classification.subcategory
  • artists[]: origin, name, externalId, spotifyId
  • public, published, suspendSales, markedAsSoldOut
  • startDate, endDate, timezone, totalCapacity
  • ticketTypes[]:
    • _id, name, price, quantity
    • priceRange.enabled, priceRange.min, priceRange.max
    • priceOptions.enabled, priceOptions.options[] (value)
    • description, disabled, deleted, isDonation
    • tickets[]: ticketTypeId, quantity
  • pricing.minimumPrice, pricing.maximumPrice
  • paymentOptions.refundSettings.refundPolicy, paymentOptions.refundSettings.customRefundPolicy
  • publishedAt
  • additionalQuestions[]: _id, inputType, question, required, description, perOrder, disabled, createdAt, updatedAt
  • bannerImage.url, featureImage.url, socialImage.url
  • eventLocation: type, venueName, address, latLng[], instructions, placeId, onlineUrl, mapUrl, city, region, country
  • dates[]: _id, startDate, endDate, scheduleId, disabled, deleted
  • packagedTickets[]: _id, name, price, quantity, description, disabled, deleted
  • packagedTickets[].tickets[]: ticketTypeId, quantity
  • accessibility:
    • contactName, contactNumber, travelInstructions, entryInstructions, afterEntryInstructions
    • hazards, toiletLocation, disabledParking
    • features.access, features.wheelchairAccessibility, features.audioDescription, features.telephoneTypewriter, features.volumeControlTelephone, features.assistiveListeningSystems, features.signLanguageInterpretation, features.accessiblePrint, features.closedCaptioning, features.openedCaptioning, features.brailleSymbol
  • affiliateCode.code
  • keywords[]
  • location
  • createdAt, updatedAt (replication)
Orders placed by users for event ticket purchases.Key Fields:
  • _id: Unique order identifier (primary key)
  • eventId: References events._id
  • userId, currency, eventDateId
  • status, financialStatus
  • firstName, lastName, organisation
  • mobile, email, accessCode
  • discounts.autoDiscount.discountAmount
  • discounts.discountCode.code, discounts.discountCode.discountAmount
  • businessPurpose, businessTaxId, businessName
  • paymentType, paymentGateway, manualOrder, tipFees
  • clientDonation, notes, organiserMailListOptIn
  • incompleteAt, completedAt, waitlistOfferId
  • isInternationalTransaction
  • totals: subtotal, amexFee, zipFee, humanitixFee, bookingFee, passedOnFee, clientDonation, netClientDonation, donation, dgrDonation, giftCardCredit, credit, outstandingAmount, feesIncluded, bookingTaxes, passedOnTaxes, taxes, totalTaxes, discounts, refunds, netSales, grossSales, referralAmount, total
  • purchaseTotals: same shape as totals
  • additionalFields[]: questionId, value, details.street, details.suburb, details.postalCode, details.city, details.state, details.country
  • salesChannel, location
  • createdAt, updatedAt (replication)
Individual tickets issued for event purchases.Key Fields:
  • _id: Unique ticket identifier (primary key)
  • eventId: References events._id
  • orderId: References orders._id
  • eventDateId, userId, currency
  • status
  • firstName, lastName, email, mobile, organisation
  • ticketTypeName, ticketTypeId
  • price
  • accessCode
  • checkedIn, checkedInAt, checkedInBy
  • checkedOut, checkedOutAt
  • refunded, refundedAt
  • cancelled, cancelledAt
  • transferred, transferredAt
  • qrCode
  • seatLabel, tableLabel
  • additionalFields[]: questionId, value, details.street, details.suburb, details.postalCode, details.city, details.state, details.country
  • salesChannel, location
  • createdAt, updatedAt (replication)
Tags from Humanitix used to categorize organizers/events.Key Fields:
  • _id: Unique tag identifier (primary key)
  • name
  • colour
  • userId, organiserId
  • createdAt, updatedAt

​
Data Model

The following diagram illustrates the relationships between Humanitix entities. The arrows indicate the join keys that link the streams.

​
Use Cases for Data Analysis

This guide outlines common analysis patterns using Humanitix data.

​
1. Ticket sales by event (last 30 days)

Track how many tickets were sold per event and the total ticket price (using the tickets stream). 
-- Replace `nekt_raw.humanitix_events` / `nekt_raw.humanitix_tickets`
-- with your configured layer + table names.
SELECT
  e.name AS event_name,
  COUNT(*) AS tickets_sold,
  SUM(t.price) AS total_ticket_price
FROM
  nekt_raw.humanitix_tickets t
JOIN
  nekt_raw.humanitix_events e
ON e._id = t.eventId
WHERE
  CAST(t.updatedAt AS TIMESTAMP) >= current_timestamp - INTERVAL '30' DAY
GROUP BY
  1
ORDER BY
  total_ticket_price DESC

​
Implementation Notes

​
Data quality considerations

  • events, orders, and tickets support incremental sync using updatedAt as the replication key.
  • tags does not provide an incremental replication key (replication_key = None), so FULL_TABLE is the appropriate sync type.
  • Nested objects and arrays (for example ticketTypes[] and additionalQuestions[]) are available as structured columns in Nekt; inspect your table schema in the Catalog or use Explorer to validate how they are represented in SQL.

​
Performance considerations

  • orders and tickets are fetched per event (/v1/events/{event_id}/...). Syncing many events can increase extraction time.
  • Use start_date to control how far back incremental history begins, and consider running incremental syncs regularly.

​
Skills for agents

Download Humanitix skills file

Humanitix connector documentation as plain markdown, for use in AI agent contexts.