Is it possible to virtualize SAP HANA tables in Azure SQL Data Warehouse? If so, please provide link to the documentation or details.
We are currently using Smart Data Access to virtualize tables between HANA tenants and it works well for our scenario. However, Data Warehouse has recently been introduced to our environment and the requirement is to have the data (virtual or replicated) in there as well.
Our current workaround is a script that replicates the data, but now we are having issues with keeping the data in sync. Moreover, we would prefer not to replicate data at all if possible.
Thanks,
Mike
No, it is not possible to virtualise Hana tables from Azure SQL Data Warehouse.
SAP customers typically export data to Azure storage, then ingest to Azure SQL Data Warehouse using the Polybase feature for fast parallel ingestion.
Related
I'm trying to access Azure Table Storage in a Gen 2 data lake from Azure SQL Server, but I can't find any documentation. Loads on how to get to csv's in blob storage, but nothing on Azure tables.
Any ideas?
John
Your requirement isn't feasible.
Azure Table storage is a service that stores non-relational
structured data (also known as structured NoSQL data) in the cloud,
providing a key/attribute store with a schemaless design.
Since, Table storage can't be queried using SQL, therefore there is no sense to access it using any SQL Server.
I recommend you to first go through Table storage concepts
before knowing how to query it.
Once getting the Table Storage structure, you can query the tables either through REST API or Cosmos DB Table API based on your application. Refer Querying tables and entities.
You can also follow this complete tutorial Quickstart: Build a Table API app with .NET SDK and Azure Cosmos DB to create basic application using Table Storage for learning purpose.
I have a situation where most of my organization's data sits at Azure SQL. Now we are including one more data source which gives 1GB of structured data daily. My objective is that I have to merge this 1GB with the Azure SQL data and give it to the PowerBI. I can't do this on PowerBi because it is slow.
Now should I choose CosmosDB as a sink and replicate some of the Azure SQL tables to CosmosDB?so that I will have stored procedure at cosmos which does the required merge and places it in the final tables at cosmos for PowerBi to pick up.
Or should I choose some other sink? (I can have appendblob but it has a 200GB upper limit. I can have Azure table storage but then how can I merge with Azure SQL data?
Any recommendations on what to do?
I need to export a multi terabyte dataset processed via Azure Data Lake Analytics(ADLA) onto a SQL Server database.
Based on my research so far, I know that I can write the result of (ADLA) output to a Data Lake store or WASB using built-in outputters, and then read the output data from SQL server using Polybase.
However, creating the result of ADLA processing as an ADLA table seems pretty enticing to us. It is a clean solution (no files to manage), multiple readers, built-in partitioning, distribution keys and the potential for allowing other processes to access the tables.
If we use ADLA tables, can I access ADLA tables via SQL Polybase? If not, is there any way to access the files underlying the ADLA tables directly from Polybase?
I know that I can probably do this using ADF, but at this point I want to avoid ADF to the extent possible - to minimize costs, and to keep the process simple.
Unfortunately, Polybase support for ADLA Tables is still on the roadmap and not yet available. Please file a feature request through the SQL Data Warehouse User voice page.
The suggested work-around is to produce the information as Csv in ADLA and then create the partitioned and distributed table in SQL DW and use Polybase to read the data and fill the SQL DW managed table.
We have shifted from IBM DB2 databases to having PostGRE SQL databases on the AWS Cloud. Is anyone aware of or has worked with AWS to test databases?
a) If so, what tools do you use?
b) What do you test when checking the databases in a Business Intelligence (BI) type of environment?
Anything other than just load or performance testing on it. I wish to check on Functional Testing, where I validation/verify that the data on the Cloud Servers and Databases is equivalent to the Data in the physical Servers with DB2 as the database.
So, mainly a kind of data reconciliation, but with ETL also involved.
Our product Ajilius (http://ajilius.com) does 90% of what you're after. We specialise in cloud data warehouse automation. PostgreSQL is our primary DBMS for on-premise and SMP data warehouses; Redshift is one of our cloud platforms (as well as Snowflake and Azure SQL Data Warehouse); and DB2 is a supported data source.
I say "90%" because our data warehouse migration feature reconciles data that is migrated between warehouses, but only when both warehouses were created by Ajilius. I'd like to understand more about your need, if you email me through our web site we can talk it over in detail.
Two competitors - Matillion and Treasure Data - also work in this space. Matillion is a full ETL tool, Treasure Data is more "EL" without the T. Definitely look at them, they're both good products with different approaches.
I've done a fair bit of reading and it seems like there are a couple of off-the-shelf products that replicate/sync data from on-premise database to Azure SQL Data Warehouse but I've found nothing that syncs using an Azure database as the source. The Azure Data Factory holds some promise however it looks more suited to one off loads.
Anyone know of a way? (SSIS package not really an option as I want the transfer to occur wholly inside the cloud)
Azure Data Factory can run continuous loads from SQL Database to SQL Data Warehouse. You'll want to look into the frequency and interval parameters for the pipeline
The documentation is here https://azure.microsoft.com/en-us/documentation/articles/data-factory-create-datasets/.