Get direct access to the complete prediction market database for advanced analytics and complex queries.
Getting Started Already have credentials? Jump to Connection Methods . New to Probalytics? Create ClickHouse credentials in app.probalytics.io → ClickHouse Credentials section. See Quickstart for setup.
Connection Details
Host : clickhouse.probalytics.ioPort : 9440 (Secure TCP) or 8443 (Secure HTTPS)Database : probalyticsAuthentication : Username and password from dashboard
All connections are secured with TLS encryption. Use the --secure flag for CLI or enable TLS/SSL in your client.
Quick Exploration SQL Workspace (Browser) The fastest way to explore and test queries. Visit app.probalytics.io/sql and start querying immediately—no setup required.
Large result sets will crash your browser. Keep queries focused and use LIMIT to restrict results. For bulk exports or large analytics, use programmatic connections instead.
Connection Methods For production applications and large-scale analysis, use one of these programmatic connections:
Native ClickHouse driver for best performance. Install: pip install clickhouse-driver from clickhouse_driver import Client client = Client( host = 'clickhouse.probalytics.io' , port = 9440 , user = 'YOUR_USERNAME' , password = 'YOUR_PASSWORD' , database = 'probalytics' , secure = True ) # Test connection result = client.execute( 'SELECT count() FROM markets;' ) print ( f "Total markets: { result[ 0 ][ 0 ] } " )
HTTP-based client, simpler setup. Install: pip install clickhouse-connect import clickhouse_connect client = clickhouse_connect.get_client( host = 'clickhouse.probalytics.io' , port = 8443 , username = 'YOUR_USERNAME' , password = 'YOUR_PASSWORD' , database = 'probalytics' ) # Test connection result = client.query( 'SELECT count() FROM markets;' ) print ( f "Total markets: { result.first_item } " )
Install: npm install @clickhouse/client import { createClient } from '@clickhouse/client' ; const client = createClient ({ url: 'https://clickhouse.probalytics.io:8443' , username: 'YOUR_USERNAME' , password: 'YOUR_PASSWORD' , database: 'probalytics' }); // Test connection const result = await client . query ({ query: 'SELECT count() FROM markets;' , format: 'JSONEachRow' }); const data = await result . json (); console . log ( `Total markets: ${ data [ 0 ]. count } ` );
Install: go get github.com/ClickHouse/clickhouse-go/v2 package main import ( " fmt " " github.com/ClickHouse/clickhouse-go/v2 " " context " " crypto/tls " ) func main () { conn , _ := clickhouse . Open ( & clickhouse . Options { Addr : [] string { "clickhouse.probalytics.io:9440" }, Auth : clickhouse . Auth { Username : "YOUR_USERNAME" , Password : "YOUR_PASSWORD" , }, TLS : & tls . Config {}, Settings : clickhouse . Settings { "max_execution_time" : 300 , }, }) var count uint64 err := conn . QueryRow ( context . Background (), "SELECT count() FROM markets;" ). Scan ( & count ) fmt . Printf ( "Total markets: %d \n " , count ) }
Popular GUI tool for SQL queries and exploration.
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Create new connection → Search “ClickHouse”
Configure:
Server Host : clickhouse.probalytics.ioPort : 8443Database : probalyticsUsername : From your dashboardPassword : From your dashboardSSL : Enable SSL/TLS in connection settings
Test connection → Browse and query tables
Quick exploration and ad-hoc queries. Install: ClickHouse Docs clickhouse client --host=clickhouse.probalytics.io --secure --port=9440 --user=YOUR_USERNAME --password=YOUR_PASSWORD --database=probalytics
Or run a query directly: clickhouse client \ --host clickhouse.probalytics.io \ --secure \ --port 9440 \ --user YOUR_USERNAME \ --password YOUR_PASSWORD \ --database probalytics \ --query "SELECT count() FROM markets;"
Exploring the Database List All Tables SHOW TABLES FROM probalytics;
Describe Table Structure DESCRIBE TABLE probalytics . markets ; DESCRIBE TABLE probalytics . trades ;
Test Your Connection SELECT 'markets' as table_name, count () as row_count FROM markets UNION ALL SELECT 'trades' as table_name, count () as row_count FROM trades;
Understanding ReplacingMergeTree Tables use the ReplacingMergeTree engine for efficient updates and deduplication.
How it works:
New versions of the same row replace old versions
Deduplication is based on the indexed_at column (highest value wins)
Background merges consolidate duplicates asynchronously
Queries may return duplicates until merges complete
The FINAL Keyword Use FINAL to force immediate deduplication:
-- May include duplicates (fast) SELECT count () FROM markets; -- Guaranteed deduplicated (slower) SELECT count () FROM markets FINAL;
FINAL triggers synchronous deduplication which is significantly slower. Use it only when you need guaranteed unique results. For most analytics, skip FINAL and rely on background merges.
Access Tiers & Limits Your tier determines available data, query limits, and resource quotas:
Feature Starter Pro Custom Tables markets, trades All tables All tables Historical Data Last 30 days Full history Full history Queries/hour 100 1,000 Unlimited Max Execution Time 5 minutes 1 hour Unlimited Max Memory 4 GB 32 GB Unlimited Max Result Rows 100,000 1 billion Unlimited
Your tier is set when creating ClickHouse credentials in the dashboard. Upgrade your plan to access higher tiers.
Available Tables markets Primary table for prediction market metadata.
Available to : All tiersRecords : One per market across platformsKey fields : platform, title, description, outcomes, dates, statusSee Tables reference for complete schema
trades Individual trade records on each market.
Available to : All tiersRecords : One per trade executedKey fields : market_id, price, volume, side, trader_id, timestampsNote : Partitioned monthly by created_at for performanceSee Tables reference for complete schema
chain_events Raw blockchain events (internal use).
Available to : Pro and Custom tiers onlyRecords : Low-level chain events from smart contractsUse case : Advanced on-chain analysisNot recommended for typical market analysis
Next Steps
Tables Reference Complete field definitions and data types
Common Queries Ready-to-run query examples
SQL Tips Performance optimization strategies
