VectorFin in BigQuery

Native Analytics Hub listing is on the roadmap (Q3 2026). Today, load via the REST API on a schedule. The snippets below show the planned shape.

10 min

Setup time

Iceberg tables

5K+

US tickers

Nightly

Updates

Prerequisites

📋VectorFin Pro plan

🔑API key from app.vectorfinancials.com

☁️BigQuery account

Connection Guide

Today: load via REST API on a Cloud Scheduler / Workflow

Until the Analytics Hub listing ships, the supported pattern is to call the REST API from a Cloud Function or Workflow on a daily schedule and write rows into a BigQuery table you own.

python

# Cloud Function (Python 3.12) — runs daily after VectorFin's pipeline
import os, requests
from google.cloud import bigquery

VF_API_KEY = os.environ["VECTORFIN_API_KEY"]
TICKERS = ["AAPL", "MSFT", "NVDA", "GOOGL", "META", "AMZN", "TSLA"]
TABLE   = "your-project.vectorfin.signals"

def main(_request):
    bq = bigquery.Client()
    rows = []
    for t in TICKERS:
        r = requests.get(
            f"https://api.vectorfinancials.com/v1/signals/{t}",
            headers={"X-API-Key": VF_API_KEY},
            params={"limit": 30},
            timeout=10,
        )
        r.raise_for_status()
        rows.extend({"ticker": t, **row} for row in r.json())
    errors = bq.insert_rows_json(TABLE, rows)
    return ("ok", 200) if not errors else (str(errors), 500)

Coming soon: subscribe to the Analytics Hub listing

The native flow (Q3 2026) will be a one-click Analytics Hub subscription: the linked dataset shows up in your project and queries hit BigQuery-managed external Iceberg tables backed by VectorFin's warehouse. Watch the changelog at vectorfinancials.com/changelog.

sql

-- Planned native flow (NOT YET LIVE — for reference only)
-- 1. In BigQuery → Analytics Hub, search for "VectorFin Signals"
--    and click Subscribe. A linked dataset is added to your project.
-- 2. The shared dataset surfaces as external Iceberg tables.
-- 3. Query directly:

SELECT ticker, date, score, components
FROM `your-project.vectorfin_shared.whystock_score`
WHERE ticker = 'AAPL'
  AND date >= DATE_SUB(CURRENT_DATE(), INTERVAL 90 DAY)
ORDER BY date DESC;

Want early access?

We're onboarding design partners for the Analytics Hub listing now. Email support@vectorfinancials.com if you want to be in the first cohort — we'll publish the listing into your billing project as soon as it's ready.

bash

# Email: support@vectorfinancials.com
# Subject: BigQuery Analytics Hub early access
# Include: GCP billing project ID + region (US, EU, etc.)

Available Tables

All 7 VectorFin data tables — bitemporal (effective_ts + knowledge_ts), append-only, nightly updates.

GET /v1/signals/{ticker}Today: REST → bq.insert_rows_json on a schedule

▼

sql

bigquery.Client().insert_rows_json("project.dataset.signals", rows)

GET /v1/embeddings/{ticker}Today: REST → write Parquet to GCS → CREATE EXTERNAL TABLE

▼

sql

bq load --source_format=PARQUET project:dataset.embeddings gs://bucket/vf_embeddings.parquet

vectorfin_shared.whystock_scoreComing soon: Analytics Hub linked dataset

▼

sql

SELECT * FROM `your-project.vectorfin_shared.whystock_score` -- Q3 2026

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