Supermetrics for Databricks
Connect Instagram to Databricks — Social Analytics on the Lakehouse


Load Instagram organic content and engagement data into Databricks for social media performance analytics.
Why Connect Instagram to Databricks?
Warehouse your Instagram data in Databricks for unlimited historical analysis and cross-source SQL.
ML content performance prediction
Build engagement prediction models on your Instagram content history using Databricks Feature Store and MLflow. Compute features like posting time, caption length, and format engagement decay — then predict which upcoming posts will maximize reach.
PySpark for cross-platform content analysis
SQL analysts query Instagram format comparisons in Databricks SQL Warehouse, while data scientists use PySpark to cluster content types by engagement patterns across Instagram, TikTok, and YouTube on the same Delta tables.
Unity Catalog governance for multi-brand accounts
Managing multiple Instagram accounts? Unity Catalog lets you apply row-level filters so each brand team sees only their own content data, with column masking on sensitive metrics and full lineage tracking from ingestion to dashboards.
How to Connect Instagram to Databricks
Three steps. Under two minutes. Zero code.
- 1
Create a data transfer
Log into Supermetrics, select your data source and Databricks as your destination.
- 2
Authorize and configure
Connect your data source account, provide your Databricks workspace URL and access token, choose your catalog and schema, and select the data you want to transfer.
- 3
Set schedule and start transfer
Choose your refresh frequency (hourly, daily, or weekly) and click Start. Your data begins flowing into Databricks Delta tables automatically.
Instagram Data Schema in Databricks
Supermetrics creates and maintains clean, typed tables automatically. Here's what your Instagram data looks like in Databricks.
Data Freshness & Scheduling
Instagram data is typically available in Databricks within 3-6 hours of the sync schedule.
What Instagram Data Can You Pull into Databricks?
Supermetrics gives Databricks access to your full Instagram reporting data — metrics and dimensions you already know from the Instagram interface.
Key Metrics
- Views
- Reach
- Likes
- Comments
- Saves
- Shares
- Follower count
- Profile visits
- Story views
- Story replies
- Reel interactions
- Total interactions
Key Dimensions
- Media type
- Media product type
- Post caption
- Published date
- Day of week
- Post URL
- Media ID
- Account name
Resources & Guides
Why Supermetrics for Databricks?
Purpose-built for marketing data since 2009. 200,000+ companies trust Supermetrics to move 15% of global ad spend into reporting and analytics destinations.
No Vendor Lock-In
Your data lands in Databricks — infrastructure you own and control. Use any BI tool, any transformation layer, any ML platform. If you ever switch providers, your data and dashboards stay with you.
170+ Marketing Data Sources
Purpose-built for marketing data — not a generic ETL tool. Supermetrics covers 99% of metrics and dimensions from each source, with pre-structured tables ready for analysis. No transformation layer required.
Incremental Loading
Only new and updated Instagram records are transferred on each run — efficient, cost-effective, and fast. Full historical backfill available on demand.
Your Data, Your Infrastructure
Supermetrics moves data directly to your destination — nothing is stored on our servers. SOC 2 Type II certified, GDPR and CCPA compliant. Your data stays in infrastructure you control, simplifying privacy and compliance reviews.
Flat-Rate, Predictable Pricing
Fixed annual pricing regardless of data volume — no per-row charges, no surprise bills during peak campaign seasons. Transfer as much Instagram data as you need without worrying about cost spikes.
Historical Depth
Access your full Instagram history — months or years of engagement data, follower growth, and content performance. No artificial date range restrictions.
Frequently Asked Questions
How do I connect Instagram to Databricks with Supermetrics?
Log into the Supermetrics Hub, create a new data transfer, select Instagram as the source and Databricks as the destination. Authorize your Instagram account, provide your Databricks workspace URL and access token, choose your catalog, schema, and Unity Catalog settings, select the fields you need, set a schedule, and start the transfer. No custom notebooks, Spark jobs, or Delta Lake plumbing required — Supermetrics writes directly to Delta tables and registers them in Unity Catalog so your data is governed, versioned, and queryable with both SQL and PySpark from the moment it lands.
Is my Instagram data secure when transferring to Databricks?
Supermetrics is SOC 2 Type II certified and fully GDPR compliant. All Instagram credentials are encrypted at rest and in transit. Data flows directly from the Instagram API into your Databricks workspace — Supermetrics never stores your marketing data on its own servers. Unity Catalog provides centralized governance: fine-grained row-level and column-level security, attribute-based access control, and a full audit log of who queried what. Delta Lake's transaction log makes every write atomic and traceable, so you always have a verifiable lineage of your Instagram data from ingestion to insight.
Can I combine Instagram data with other sources in Databricks?
That is one of the defining advantages of the Databricks lakehouse architecture. Once Instagram data lands as a Delta table, you can JOIN it with any other table in your lakehouse — raw event streams, CRM exports, product analytics, even ML Feature Store tables used for model training. Query in SQL from Databricks SQL warehouses or switch to PySpark and pandas for data science workflows — same data, no copying. Supermetrics supports 170+ connectors that all land in the same Unity Catalog namespace, and the Photon engine accelerates analytical queries on those Delta tables automatically.
What Instagram metrics and dimensions are available in Databricks?
All standard Instagram reporting fields are available, including Views, Reach, Likes, Comments, Saves, Shares, and many more. You select exactly which metrics and dimensions to transfer during setup, and you can add or remove fields at any time without losing historical data already stored in your Delta tables. Delta Lake's time travel lets you query any previous version of your Instagram data — useful for auditing retroactive metric recalculations or reproducing a dashboard state from last quarter. Schema evolution is handled automatically, so new fields appear as columns without breaking existing queries.
How fresh is Instagram data in Databricks?
Data freshness depends on your transfer schedule. Supermetrics supports hourly, daily, or weekly transfers into Databricks. Most teams schedule daily transfers so yesterday's complete data is available each morning. Delta Lake's MERGE capability ensures only new and changed records are upserted, keeping cluster utilization and storage costs low. For teams that need near-real-time visibility, the Photon engine accelerates incremental queries so dashboards refresh in seconds, and you can set up Databricks SQL alerts to trigger notifications when key Instagram metrics cross your thresholds.
Does the Instagram connector include Reels data?
Yes. Reel plays, likes, comments, shares, saves, and reach are all available as metrics in your Delta tables.
Can I track follower growth over time in Databricks?
Yes. Follower count is captured with each sync, allowing you to build time-series growth analysis with SQL.
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