Most marketing teams that use Google BigQuery pay nothing. The free tier covers the majority of standard marketing use cases. But to understand why, you need to know what BigQuery charges for and what it does not.
What BigQuery Charges For
BigQuery charges for three things:
- Data storage: the cost of storing your tables and datasets inside BigQuery.
- Query processing: the cost of running SQL queries against your data.
- Streaming inserts: the cost of sending real-time data into BigQuery.
BigQuery does not charge you for importing data or exporting data. Loading data from your ad platforms into BigQuery is free.
The BigQuery Free Tier
Google gives every BigQuery user a permanent free tier every month:
10GB of active storage free.
1TB of query processing free.
These are not trial limits. They reset every month, forever.
For most marketing teams, 10GB of storage holds months or years of ad performance data. And 1TB of query processing covers hundreds of standard marketing queries per day.
The result: most small and mid-size marketing teams pay $0 per month to use BigQuery.
What You Pay When You Exceed the Free Tier
If your data or query volume grows beyond the free tier, here is what BigQuery charges:
- Storage: $0.02 per GB per month for active storage. If you store 100GB of data, you pay $1.80 per month (the first 10GB is free, so you pay for 90GB).
- Query processing: $5 per TB processed. If you run queries that process 5TB of data in a month, you pay $20 (the first 1TB is free, so you pay for 4TB).
- Streaming inserts: $0.01 per 200MB of data streamed in real time. This applies only if you are sending live data to BigQuery. For daily batch loads from ad platforms, this cost is zero.
How to Stay on the Free Tier
Most marketing teams stay within the free tier by following a few simple practices.
Load data in batches, not in real time. Daily batch loads from your ad platforms are free. Real-time streaming inserts cost money. For marketing reporting, daily data is sufficient.
Write efficient SQL queries. BigQuery charges based on how much data your query scans, not how long it takes to run. A query that scans your entire table costs more than a query that filters to a specific date range. Adding a date filter to your queries reduces the data scanned and keeps costs low.
Set up budget alerts. In Google Cloud, you set a monthly budget and BigQuery sends you an alert if your spending approaches that limit. This prevents unexpected charges.
Use partitioned tables. When your tables are partitioned by date, BigQuery scans only the relevant partitions when you filter by date. This reduces query costs significantly.
BigQuery Cost vs Other Data Warehouses
Snowflake, Amazon Redshift, and Azure Synapse all offer trials, but not permanent free tiers. Once your trial ends, you pay for compute and storage regardless of how much you use. For a team running standard marketing queries, costs on those platforms typically start at $500 per month or more.
BigQuery’s free tier and pay-per-query model make it the most cost-effective data warehouse for marketing teams that are starting out or running at moderate scale.
Estimating Your BigQuery Cost
If you want to estimate your costs before you start, here is a simple framework:
For a marketing team with 5 to 10 ad accounts across Meta, Google Ads, TikTok, and LinkedIn, your daily data load is typically 50MB to 200MB. Over a month, that is 1.5GB to 6GB of new data. Well within the 10GB free tier.
For queries, a standard marketing dashboard that runs 10 to 20 queries per day typically processes 5GB to 50GB of data per month. Well within the 1TB free tier.
Most marketing teams using Porter Metrics to load their data into BigQuery stay within the free tier indefinitely.
Getting Started With BigQuery for Free
To start using BigQuery, you need a Google Cloud account with a billing account attached. Google requires a billing account even for free-tier usage. You will not be charged unless you exceed the free limits.
Porter Metrics connects your marketing data to BigQuery automatically. You connect your ad accounts, select your data, and Porter loads everything into BigQuery on a daily schedule. No streaming inserts, no unexpected costs.
Ready to connect your marketing data to BigQuery?
Porter Metrics makes it easy to sync all your sources — no code required.