I am trying to test out Azure Purview and connect it to an Azure SQL Server. Since the SQL server is hosted in the cloud I want to use the default AutoResolve Integrated Runtime to get connected but there is not one setup or an option to setup a new one. Has anyone else using Purview been able to setup (or needed to setup) an AutoResolve IR?
To connect to Azure SQL DB/MI you can directly go to the Azure Purview portal and register new data sources and select Azure SQL DB/MI.
In this article - Manage data sources in Azure Purview (Preview), you learn how to register new data sources, manage collections of data sources, and view sources in Azure Purview (Preview).
Only to connect on-premise SQL server you need to Set up a
self-hosted integration runtime to scan the data source.
If the data source is located on Azure, you don't need any integration runtime to scan the data source.
Reference: Register and scan an Azure SQL Database.
CHEEKATLAPRADEEP-MSFT is absolutely correct, to go a step further, since you know what an auto resolve integration runtime is, you probably are utilizing Azure Data Factory so in addition to registering your SQL Server, you can also link your Azure Data Factory for data lineage purposes. Based on the pipelines that are executed, it will autonomously create the data lineage.
Navigation to Link Data Factory
Data lineage created by linking Data Factory
Keep in mind, you will have to execute pipelines after linkage for it to pick up the data lineage. Also, for sources or destinations not supported yet, it will not get the data lineage.
Related
I m new to Azure Data Factory. How Can I create a C# object in Azure data factory and I m not sure how we can create an SQL connection in ADF? Somebody please guide me on this?
Thanks #Peter Bons for the valuable suggestions on this.
Follow the below detailed process to achieve your requirement.
Create an Azure data factory from the Portal.
Create SQL Server & Azure Storage linked services with a self-hosted integration runtime.
From the Azure Data Factory Studio launch the Data Factory UI in new tab.
Select the SQL Server from the new dataset in pipeline.
Create New linked service (SQL Server) and test the connection, it will show you Connection Successful once we given all the required values.
Linked Service Screenshot:
References:
Copy data from a SQL Server database to Azure Blob storage by using Azure Data Factory.
Create an Azure SQL Database linked service using UI.
Is it possible for me to insert some data from one database to another in Azure sql?
Let's say I have a trigger in db1 that updates some values in db2.
I read about elastic queries but it seems like they are read-only so they don't solve my problem.
You can't use cross-database in Azure Sql Server because databases can't see eachother physically , you could use elastic pools but they are Read Only.
A solution is to use SQL Managed Instance to upload your instance . This supports cross-database queries but it was expensive.
There was some previous discussion here about doing similar:
C# Azure Function trigger when SQL Database has a new row added without polling
There is also the Azure SQL Bindings for Azure Functions but they are input bindings and not triggers and they're still in preview and limited to C#, JavaScript and Python.
Azure SQL bindings for Azure Functions overview (preview)
There was a new announcement last week after MS Build however for Azure SQL Database External REST Endpoints Integration (hopefully they don't refer to it as ASDEREI) but this is currently in preview under Early Adoption Program (EAP).
Announcing the “Azure SQL Database External REST Endpoints Integration” Early Adoption Program
What are possible solutions to do per-request or on schedule 1-way sync of one SQL Server database to the other in Azure?
Both DBs are configured to allow access only via private endpoints.
I've just started exploring options, appreciate expert's opinion on the question.
1-way replication, incrementally data sync and on schedule configuration -- Azure Data Factory is the most suitable service to achieve the following requirements.
Using ADF, you can incrementally load data from multiple tables in a SQL Server Database to one or more databases in another or same SQL Server by creating pipeline using Copy activity. You can also schedule the pipeline trigger based on your requirement.
This official tutorial from Microsoft on Incrementally load data from multiple tables in SQL Server to a database in Azure SQL Database using the Azure portal will help you to create the ADF environment using Linked Service, Datasets, and copy Activity to accomplish your requirement (skip setting Self hosted Integration Runtime as it is required when one of your database is in on-premises).
Once your pipeline has been created, you can schedule it by creating New Trigger. Follow Create a trigger that runs a pipeline on a schedule to create new trigger.
We are working on implementing a new project in Azure. The idea is to move out of on-premise systems into the cloud as we have our vendors, partners and clients moving into the cloud. The option we are trying out is to use Azure Data Share and have Azure SQL Database subscribe to the data.
The thing we are now trying to explore is once a new data snapshot is created how do we import this data into Azure SQL Database?
For instance we have Partner information and this information is made available via Azure Data Share and new data snapshot is created daily.
The part that I am not sure of is how to synchronize this data between Azure Data Share and Azure SQL Database.
Also, Is there an api available to expose this data out to external vendors, partners or clients from Azure SQL Database after we have data sync to Azure SQL Database from Azure Data Share?
Azure Data Share -> Azure SQL Database
Yes, Azure SQL Database is a supported.
Azure Data Share -> SQL Server Database (on-prem)? Is this option supported?
No, SQL Server Database (on-prem) is not supported.
Is there an api that could be consumed to read data?
Unfortunately, there is no such API that could be consumed to read data.
Azure Data Share enables organizations to simply and securely share data with multiple customers and partners. In just a few clicks, you can provision a new data share account, add datasets, and invite your customers and partners to your data share. Data providers are always in control of the data that they have shared. Azure Data Share makes it simple to manage and monitor what data was shared, when and by whom.
Azure Data Share helps enhance insights by making it easy to combine data from third parties to enrich analytics and AI scenarios. Easily use the power of Azure analytics tools to prepare, process, and analyze data shared using Azure Data Share.
Which Azure data stores does Data Share support?
Data Share supports data sharing to and from Azure Synapse Analytics, Azure SQL Database, Azure Data Lake Storage, Azure Blob Storage, and Azure Data Explorer. Data Share will support more Azure data stores in the future.
The below table details the supported data sources for Azure Data Share.
How to synchronize this data between Azure Data Share and Azure SQL Database.
You need to choose “Snapshot setting” to refresh data automatically.
A data provider can configure a data share with a snapshot setting. This allows incremental updates to be received on a regular schedule, either daily or hourly. Once configured, the data consumer has the option to enable the schedule.
I'm following the instructions to set up App Insights to spool to SQL using Azure Stream Analytics, but I'm trying to deviate slightly to use an on-premise SQL server (that the web application already uses) over VPN.
At the point of adding the output, this is failing with:
Is it the case that IP addresses are not supported, or is it something more fundamental than that?
You are probably looking for answers directly to your question, which Jean-Sébastien answers succinctly. But an alternative architecture, if you haven't considered it already...
You could stream to a transient Azure SQL Database or Blob storage (likely cheaper depending on your workload), and then use Azure Data Factory tunnelled via a Self-Hosted Data Factory Integration Runtime to "send" the data back to on-premise SQL.
Data Factory V2 also has blob triggers, so rather than needing a schedule it could pickup any new blobs in micro batches.
I say "send" in quotation marks as the Integration Runtime actually creates an outgoing connection to from on-premise to Azure, yet gives the capability for push-like data transfer.
If data factory proves useful, here is a guide creating copy pipelines: https://learn.microsoft.com/en-us/azure/data-factory/tutorial-hybrid-copy-portal
Albeit this guide is for on-prem sql to blob, but it gives you a stronger starting point.
At this time only Azure SQL Databases are supported in Azure Stream Analytics.
Sorry for the inconvenience.
Thanks,
JS (Azure Stream Analytics)