How to handle BigQuery mirroring when the source has more than 1,000 tables?

Question

How to handle BigQuery mirroring when the source has more than 1,000 tables?

VIGNESH G 40

Hi,

We are setting up database mirroring in a Microsoft Fabric workspace, with BigQuery as the source.

Currently, our BigQuery source contains 1,193 tables, but a single mirrored database supports a maximum of 1,000 tables. Because of this limitation, we are currently able to mirror only 1,000 tables.

Our requirement is to mirror the complete source, including new tables that may be created in BigQuery in the future.

Could you please suggest the recommended approach for this scenario?

Specifically:

How can we mirror more than 1,000 BigQuery tables?

Is it recommended to create multiple mirrored databases and split the tables between them?

If we use multiple mirrored databases, how can we ensure that newly created tables in BigQuery are also automatically included in the mirroring?

Is there any other recommended approach or workaround for this limitation?

Any guidance or best practices would be greatly appreciated.

Thanks!

Himaja Y 275 Reputation points Microsoft External Staff Moderator

2026-09-02T11:42:20.5466667+00:00
HI @VIGNESH G ,

Thank you for reaching out to the Microsoft Q&A forum.

The 1,000-table limit per mirrored database is currently a platform limitation in Fabric mirroring. Since your BigQuery source contains 1,193 tables, you'll need to split the workload across multiple mirrored databases to mirror all tables.

Recommended approach:

Create multiple mirrored databases and distribute the tables between them (for example, by schema, domain, or business function).

Keep each mirrored database below the 1,000-table limit.

Monitor newly created BigQuery tables and add them to the appropriate mirrored database as needed.

Important: There is currently no built-in mechanism to automatically redistribute tables across mirrored databases once the limit is reached. If your environment frequently adds new tables, consider implementing a monitoring/automation process to identify and onboard new tables.

For long-term scalability, organizing tables logically across multiple mirrored databases is the recommended design pattern until support for larger table counts is available.

I hope this helps! Please let us know if you need any assistance from my side.
Himaja Y 275 Reputation points Microsoft External Staff Moderator

2026-09-03T14:31:19.3933333+00:00

Hi @VIGNESH G ,

I hope you had a chance to review the information shared earlier, and I hope this information has been helpful! If you still have questions, please let us know what is needed in the comments so the question can be answered.

2 answers

Your answer

Himaja Y 275 Reputation points Microsoft External Staff Moderator

2026-09-02T11:42:20.5466667+00:00

HI @VIGNESH G ,

Thank you for reaching out to the Microsoft Q&A forum.

The 1,000-table limit per mirrored database is currently a platform limitation in Fabric mirroring. Since your BigQuery source contains 1,193 tables, you'll need to split the workload across multiple mirrored databases to mirror all tables.

Recommended approach:

Create multiple mirrored databases and distribute the tables between them (for example, by schema, domain, or business function).

Keep each mirrored database below the 1,000-table limit.

Monitor newly created BigQuery tables and add them to the appropriate mirrored database as needed.

Important: There is currently no built-in mechanism to automatically redistribute tables across mirrored databases once the limit is reached. If your environment frequently adds new tables, consider implementing a monitoring/automation process to identify and onboard new tables.

For long-term scalability, organizing tables logically across multiple mirrored databases is the recommended design pattern until support for larger table counts is available.

I hope this helps! Please let us know if you need any assistance from my side.
Himaja Y 275 Reputation points Microsoft External Staff Moderator

2026-09-03T14:31:19.3933333+00:00

Hi @VIGNESH G ,

I hope you had a chance to review the information shared earlier, and I hope this information has been helpful! If you still have questions, please let us know what is needed in the comments so the question can be answered.

Answer 1

kagiyama yutaka 5,165

I think Fabric mirrored db stops at 1,000 tables, and that limit can’t be raised. When BigQuery has more, run two mirrored dbs and a small job that reads the bq table list and adds new tables to whichever mirror still has room. That’s enough to keep the source covered as it grows, and Fabric doesn’t offer another way to go past the 1,000‑table limit.

0 comments

Answer 2

Senthil kumar 2,245

Hi @VIGNESH G

I understand your concern. I will explain you what are ways to fix this issue.

First and best approach, split your BigQuery into two queries 1) 1000 tables 2) 193 tables. suppose you now the table count this is approach is best. from function or any script get the table count and implement this approach.
Use Fabric Data Pipelines or Use a scheduled notebook or Use Azure Functions or Cloud Functions.

Thanks.

0 comments