How do I replicate Apache Iceberg data to Databricks?

Sign up for Weld, connect Apache Iceberg as a source and Databricks as a destination. Weld handles the extraction, loading, and lets you transform data using SQL or dbt.

What Apache Iceberg data can I replicate to Databricks?

You can replicate the objects the Apache Iceberg connector exposes. The available objects depend on your Apache Iceberg account permissions and configuration.

How often does Weld replicate data from Apache Iceberg?

Sync frequency depends on your Weld plan. Schedules range from every 5 minutes to daily intervals. Each sync processes only new and changed data.

Can I transform Apache Iceberg data before it lands in Databricks?

Yes. Weld supports SQL-based transformations in the platform and integrates with dbt Cloud. You can clean, join, and model your data before analysis.

Is the Apache Iceberg to Databricks integration secure?

Yes. Weld encrypts all data in transit and at rest, is SOC 2 Type II certified, and supports IP whitelisting. Credentials are stored encrypted and never logged.

Apache Iceberg to Databricks integration

Replicate your Apache Iceberg data into Databricks with Weld. Automatically replicate the tables you choose from Apache Iceberg into Databricks, keeping your analytics layer up to date and ready for querying.

Start for free

4.8 on G2

Source

Weld

Warehouse

Weld · New sync

SourceApache IcebergConnected

Tables to sync

Your own tables, picked when you set up the sync.

Extract
Load
Keep in sync

DestinationDatabricksReady

iceberg schema

iceberg.Synced
iceberg.Syncing
iceberg.Synced
iceberg.Synced

Trusted by data and AI teams

How it works

How to set up Apache Iceberg to Databricks in Weld.
In the app, with the API or an agent.

API guide MCP docs

Weld · New Apache Iceberg sync

New connectionApache IcebergAuthorised

Connection nameiceberg

AuthorizeOpens Apache Iceberg to grant read access

Use cases

Why replicate Apache Iceberg to Databricks?
Ready for analysis.

Centralizing your Apache Iceberg data in Databricks lets you join it with other data sources for cross-platform analytics and deeper insights.

Build reliable dashboards and reports by querying Apache Iceberg data directly in Databricks using SQL or your preferred BI tool.

Consolidate data from Apache Iceberg alongside other databases and applications in a single cloud data warehouse for a unified analytical layer.

Database replication for analytics
Replicate your Apache Iceberg production data to Databricks without impacting database performance. Query historical data without load on your primary database.
Centralized data warehouse
Bring Apache Iceberg data into Databricks alongside other sources to create a single source of truth for your organization.
Automated reporting
Replace manual exports and spreadsheet-based reporting with automated pipelines from Apache Iceberg to Databricks. Connect BI tools like Looker, Metabase, or Power BI.

Data

What data can you replicate?
From Apache Iceberg to Databricks.

Weld syncs the objects the Apache Iceberg connector exposes into Databricks, and you choose which tables and fields to include. The connector's docs list what is available.

Weld MCP server

Ask your agent.
It queries Databricks for you.

Connect Claude, Cursor, ChatGPT or your own agent to Weld over MCP. It reads the Apache Iceberg context, finds the tables it needs and runs the query in Databricks.

Set up the MCP server

Claude CodeOpus 5

ConnectedWeld MCP

Which Apache Iceberg tables do we have in Databricks, and which is the largest?

Looking up what Weld has synced from Apache Iceberg.

●weld·search_available_references

⎿raw.iceberg.*

tables, columns and freshness

●weld·get_reference_schema

⎿columns, types and nullability

●weld·run_query

⎿select count(*) from {{raw.iceberg.…}}

submitted

●weld·get_query_status

⎿DONE

●weld·get_query_result

⎿rows returned

✓Answered from Apache Iceberg data in Databricks

>Ask about your Apache Iceberg dataMCP

Under the hood

Technical considerations.
What to expect.

Incremental syncing: Weld uses incremental syncing where supported by the Apache Iceberg API, loading only new and updated records to minimize data transfer and warehouse costs.
Change data capture: For Apache Iceberg, Weld can use log-based replication (CDC) to capture inserts, updates, and deletes without querying the entire table on every sync.
Schema handling: Weld automatically manages schema changes. If Apache Iceberg adds new fields, they're detected and added to the corresponding Databricks tables.
Data freshness: Sync frequency depends on your Weld plan. Most connectors support schedules from every 5 minutes up to daily intervals.
Security: All data is encrypted in transit (TLS) and at rest. Weld is SOC 2 Type II compliant and supports IP whitelisting for database connections.

Resources

Keep reading.
Guides, docs and schema.

Documentation

Databricks setup guide

How to connect Databricks to Weld, step by step.

Connector

Apache Iceberg connector

Everything Weld does with Apache Iceberg.

Connector

Databricks connector

Everything Weld does with Databricks.

FAQ

Common questions.
About Apache Iceberg to Databricks.

Start syncing Apache Iceberg to Databricks.

Set up your Apache Iceberg data pipeline in minutes. No credit card required. Free for 14 days.

Source

Weld

Warehouse

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Related integrations.
More with Apache Iceberg and Databricks.

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Apache Iceberg to Databricks integration

How to set up Apache Iceberg to Databricks in Weld.In the app, with the API or an agent.

Why replicate Apache Iceberg to Databricks?Ready for analysis.

Database replication for analytics

Centralized data warehouse

Automated reporting

What data can you replicate?From Apache Iceberg to Databricks.

Ask your agent.It queries Databricks for you.

Technical considerations.What to expect.

Keep reading.Guides, docs and schema.

Common questions.About Apache Iceberg to Databricks.