Indexing Polymarket with Goldsky

On April 28, 2026, Polymarket migrated to a v2 set of contracts and is no longer using subgraphs going forward. Existing public subgraph endpoints will return incomplete or incorrect data. Turbo Pipelines with the v2 Polymarket datasets are the recommended way to access on-chain Polymarket data.

Overview

Goldsky provides high-performance data infrastructure for Polymarket, making it easy to extract, transform, and load on-chain data to power both application and analytics use cases via Turbo Pipelines (real-time data replication pipelines). Polymarket is the world’s largest prediction market platform, enabling users to trade on the outcome of real-world events. Built on Polygon, Polymarket processes millions of trades and provides deep liquidity for markets spanning politics, sports, economics, and more.

Benefits

Goldsky’s Polymarket integration enables:

Real-time market monitoring - Track order fills, matched orders, and position changes as they happen
Analytics and insights - Build dashboards showing open interest, trading volume, and market trends
User position tracking - Monitor individual user balances and positions with PnL data
Trading activity analysis - Analyze granular order flow and market maker activity
Custom alerts - Set up webhooks for specific market events or trading patterns

Getting started

To use Goldsky, you’ll need to create an account, install the CLI, and log in.

Install Goldsky's CLI and log in

Install the Goldsky CLI: For macOS/Linux:
```
curl https://goldsky.com | sh
```
For Windows:
```
npm install -g @goldskycom/cli
```
Windows users need to have Node.js and npm installed first. Download from nodejs.org if not already installed.
Go to your Project Settings page and create an API key.
Back in your Goldsky CLI, log into your Project by running the command goldsky login and paste your API key.
Now that you are logged in, run goldsky to get started:
```
goldsky
```

Turbo Pipelines

Turbo pipelines allow users to replicate data into their own infrastructure (any of the supported sinks) in real time. For a complete overview of how to deploy Turbo pipelines, including a video walkthrough, check the Quickstart guide.

Working with Polymarket datasets

Goldsky provides real-time streaming of Polymarket datasets, including all historical data. The following datasets are currently available:

Dataset	Description
*Order Filled (recommended)*	Emitted when a single Polymarket order is partially or completely filled. For example: a 50¢ YES buy for 100 YES matched against a 50¢ YES sell for 100 YES will emit 2 Order Filled events, from the perspective of the YES buy and of the YES sell. This is useful for granular tracking of trading activity and history.
Orders Matched	Emitted when a Polymarket taker order is matched against a set of Polymarket maker (limit) orders. For example: a 50¢ YES buy for 200 YES matched against 2 50¢ YES sells for 100 YES each will emit a single Orders Matched event. Orders Matched gives a more high-level view of trading activity as it only tracks taker activity.
User Balances	Keeps track of all user outcome token positions.
User Positions	Keeps track of outcome token positions along with PnL-specific data including average price and realized PnL.

These datasets can be used as sources in your Turbo pipelines to stream Polymarket data to any of the supported sinks.

Dataset schemas

polymarket.order_filled

Column	Type	Description
`id`	string	Unique event identifier
`block_number`	long	Block number of the event
`block_timestamp`	long	Unix timestamp of the block
`transaction_hash`	string	Transaction hash
`address`	string	Contract address that emitted the event
`user_id`	string	Address of the user whose order was filled
`asset`	string	Token ID of the outcome token
`amount_usdc`	double	USDC value of the fill
`amount_shares`	double	Number of outcome token shares filled
`price`	double	Fill price (between 0 and 1)
`tx_type`	string	Transaction type (e.g. `TRADE`)
`side`	string	Order side (`BUY` or `SELL`)
`order_hash`	string	Hash of the order
`counterparty_id`	string	Address of the counterparty
`order_type`	string	Whether this order was `maker` or `taker`
`fee`	double	Fee paid for this fill
`builder`	string	Builder address if applicable

polymarket.orders_matched

Column	Type	Description
`id`	string	Unique event identifier
`block_number`	long	Block number of the event
`block_timestamp`	long	Unix timestamp of the block
`transaction_hash`	string	Transaction hash
`address`	string	Contract address that emitted the event
`user_id`	string	Address of the taker
`asset`	string	Token ID of the outcome token
`amount_usdc`	double	Total USDC value of the matched trade
`amount_shares`	double	Total number of outcome token shares matched
`price`	double	Effective price (between 0 and 1)
`tx_type`	string	Transaction type (e.g. `TRADE`)
`side`	string	Taker order side (`BUY` or `SELL`)
`order_hash`	string	Hash of the taker order

polymarket.user_balances

Column	Type	Description
`id`	string	Unique balance record identifier
`owner_address`	string	Address of the token holder
`contract_address`	string	ERC-1155 contract address
`token_id`	string	Outcome token ID
`token_type`	string	Token standard (e.g. `ERC_1155`)
`block_number`	long	Block number of the last update
`block_timestamp`	long	Unix timestamp of the last update
`balance`	decimal	Current token balance

polymarket.user_positions

Column	Type	Description
`vid`	long	Internal version ID
`block_range`	string	Block range for which this record is valid
`id`	string	Unique position identifier (`{user_address}-{token_id}`)
`user`	string	Address of the user
`token_id`	decimal	Outcome token ID
`amount`	decimal	Current position size
`avg_price`	decimal	Average entry price
`realized_pnl`	decimal	Realized profit and loss
`total_bought`	decimal	Total amount bought
`_gs_chain`	string	Chain identifier (e.g. `matic`)
`_gs_gid`	string	Goldsky internal graph ID

Deploying Polymarket pipelines

Turbo pipelines are defined using YAML configuration files and deployed via the Goldsky CLI. Here’s the workflow:

Create a pipeline configuration file - Define your sources, transforms, and sinks in a YAML file
Validate your configuration - Run goldsky turbo validate polymarket-pipeline.yaml to check for errors
Deploy the pipeline - Run goldsky turbo apply polymarket-pipeline.yaml to deploy
Monitor your pipeline - Use goldsky turbo logs polymarket-pipeline.yaml to view logs and goldsky turbo inspect polymarket-pipeline.yaml to see live data

For a complete walkthrough, see the Turbo Pipelines Quickstart.

Remember to first create a Secret in order for Turbo Pipelines to be able to write the data into the database of your choice. For webhook sinks, you can include authentication headers directly in the configuration.

Example pipeline configuration

Here’s an example configuration file for streaming Polymarket order fills to a webhook endpoint, using the v2 dataset and a block number range to backfill a specific period:

polymarket-orders-webhook.yaml

name: polymarket-orders-webhook
resource_size: s

sources:
  order_filled:
    type: dataset
    dataset_name: polymarket.order_filled
    version: 2.0.0
    start_at: earliest
    filter: block_number >= 42598795 AND block_number <= 42835303

transforms:
  high_value_orders:
    type: sql
    primary_key: id
    sql: |
      SELECT 
        id,
        block_number,
        block_timestamp,
        transaction_hash,
        user_id,
        asset,
        side,
        price,
        amount_usdc,
        amount_shares
      FROM order_filled
      WHERE amount_usdc > 1000

sinks:
  webhook_alerts:
    type: webhook
    from: high_value_orders
    url: https://api.example.com/polymarket/orders
    one_row_per_request: true
    headers:
      Authorization: Bearer YOUR_API_TOKEN
      Content-Type: application/json

This pipeline:

Streams Order Filled events from the v2 Polymarket dataset for a specific block range
Filters for high-value orders (amount_usdc > 1000)
Sends each order individually to your webhook endpoint with authentication

Deploy the pipeline by running:

goldsky turbo apply polymarket-orders-webhook.yaml

Fast scan is supported on the v2 Polymarket datasets, so you can backfill a specific period using a block_number range filter as shown above. Filtering by timestamp is not supported for fast scan — use block_number instead.

Note: The datasets output large amounts of data. E.g. user positions may be up to 1.2B entities to backfill, and up to 150M entities monthly to maintain. For insights on costs for datasets, please refer to our pricing calculator.

Getting support

Can’t find what you’re looking for? Reach out to us at support@goldsky.com for help.

Chains

Partners

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Indexing Polymarket with Goldsky

Overview

Benefits

Getting started

Turbo Pipelines

Working with Polymarket datasets

Dataset schemas

Deploying Polymarket pipelines

Example pipeline configuration

Getting support

Chains

Partners

Other networks

Documentation Index

​Overview

​Benefits

​Getting started

​Turbo Pipelines

​Working with Polymarket datasets

​Dataset schemas

​Deploying Polymarket pipelines

​Example pipeline configuration

​Getting support

Overview

Benefits

Getting started

Turbo Pipelines

Working with Polymarket datasets

Dataset schemas

Deploying Polymarket pipelines

Example pipeline configuration

Getting support