So for my Azure cloud-hosted application, I am using two databases, primary and secondary, respectively. The old data in the primary db is set up to be moved to the secondary db after it is not needed anymore. As a result, the secondary db with the bulk amount of data over a period of time takes a long enough time to be accessed through the SQL queries which is undesired.
So I have stored the secondary db's older data in azure cold storage and now I am trying to figure out a way to access it through SQL queries from the cold storage itself. But even though, through SSMS, connection to Azure cold storage is possible, I am not getting any option to run SQL queries since I am connected to Azure storage account, not a database engine.
Is there any solution to this? Or ANY workaround?
My aim is to store that unnecessary secondary db data in the Azure cold storage and access it from there through SQL queries whenever needed.
Any suggestion is welcome. Thanks in advance.
Related
I am a Data Warehouse developer currently looking into using the Azure platform to host a new Data Warehouse.
My experience is with using on premise servers hosting standard SQL Server Databases, one for the staging database and one for the Data Warehouse. Typically I would use a combination of SSIS and stored procedures running in a scheduled SQL server agent job for the ETL.
How can I replicate this kind of setup within Azure?
The storage size will be less than 1TB so could I just use Azure SQL Server Database over Azure SQL Data Warehouse?
If so would I need separate databases for staging and the data warehouse using the elastic pool option?
The data that I will be loading into staging will all be on premise. Will SSIS still be suitable for loading to Azure or will Azure Data Factory be a better fit?
Any help at all would be greatly appreciated! Thanks.
Leon has lots of good information there. But from a Data Warehouse perspective, I wouldn't use Data Sync for ETL purposes (mensioned as "not preferred" in the link Leon provided, Data Sync, in the list "When to use Data Sync").
For DW, Azure DB is a good option. Azure SQL Data Warehouse (known as Azure Synapse Analytics nowadays) is a heavy duty beast for handling DW. Are you really sure you need this kind of system with < 1Tb data? I'd personnally leave Azure Synaptics for now, and tried with Azure DB first. It's a LOT cheaper and you can upgrade later if necessary.
One thing to note about Azure DB though: Azure DB doesn't support queries over databases. That's not a deal breaker though, everything can be handled in the same database. I personally use a schema to differentiate staging from the DW (and of course I use other schemas in the DW as well). It's not very difficult to use separate databases of course, but the border between them is a lot deeper in Azure DB than on-premise SQL Server or other Azure solutions (Managed Instance for example).
SSIS is still an option, but the problem is, what you use to run the packages? There are options like:
continue running them from on-premise (all the hard work is still done in the cloud)
rent a VM with SQL Server from Azure, deploy the packages to the VM and run them from VM
use Data Factory to run the SSIS packages
None of those are a perfect solution for every use case. First two options come with quite a heavy cost, if running SSIS is the only thing you need them for. Using Data Factory to run SSIS is a bit cumbersome at the moment, but it's an option anyway.
Data Factory itself is a good option as well (I haven't personally tried it, but I have heard good things about it). If you use Data Factory to run your SSIS, why not start using Data Factory without SSIS packages in the first place? Of course Data Factory has some limitations compared to SSIS which might be the reason, but if your SSIS packages are simple enough, why not give Data Factory a try.
I would suggest you using Azure SQL database. It provides many price tier with difference storage for you. You can select the most suitable price tier for you. Azure SQL database also support scale up/down base on the usage.
Ref: Service tiers in the DTU-based purchase model
And as you said, the data that I will be loading into staging will all be on premise.
Azure SQL database has the feature Data Sync can help you do that:
Data Sync is useful in cases where data needs to be kept updated across several Azure SQL databases or SQL Server databases. Here are the main use cases for Data Sync:
Hybrid Data Synchronization: With Data Sync, you can keep data
synchronized between your on-premises databases and Azure SQL
databases to enable hybrid applications. This capability may appeal
to customers who are considering moving to the cloud and would like
to put some of their application in Azure.
Distributed Applications: In many cases, it's beneficial to separate
different workloads across different databases. For example, if you
have a large production database, but you also need to run a
reporting or analytics workload on this data, it's helpful to have a
second database for this additional workload. This approach minimizes
the performance impact on your production workload. You can use Data
Sync to keep these two databases synchronized.
Globally Distributed Applications: Many businesses span several
regions and even several countries/regions. To minimize network
latency, it's best to have your data in a region close to you. With
Data Sync, you can easily keep databases in regions around the world
synchronized.
When you create the SQL database, you can migrate the schema or data to Azure with many tools, such as Data Migration Assistant(DMA).
Then Set up SQL Data Sync between Azure SQL Database and SQL Server on-premises, it will help sync the data auto every 5 mins.
Hope this helps.
If you want to start on the less expensive options in Azure, go with a general purpose SQL database and an Azure Data Factory pipeline with a few activities.
Dynamic Resource Scaling ETL
You can scale up the database by issuing an alter database statement and then move onto your stored proc based ETL. I would even use a "master" proc to call the dimension and fact proc's to control the execution flow. Then scale down the database with another alter database statement. I even created my own stored proc to issue these scaling statements.
You also cannot predict when the scaling will be completed, so I have a wait activity. You could be a little more nerdy with a loop that checks the service objective property and then proceeds when it is complete. But it was just easier to wait for 10 minutes. I have only been burnt a couple times when the scaling took longer.
Data Pipeline Activities:
Scale up, proceed if successful
Wait about 10 minutes, proceed always
Execute the ETL, proceed always
Scale down
Elastic Query
You can query across databases with vertical partition Elastic Query. Performance isn't great, and they don't recommend it for ETL, but it will work. To improve performance try dumping any large table you need into a temp table and then transform the data locally.
I have a minuscule Amazon RDS instance running SQL Server and its storage almost reached the maximum allowed free tier storage of 20GB.
I have read that this might be due to the db logs. I am only using the db to get acquainted to RDS so I don't think I need any logs at the moment.
But I cannot find a way to remove the logs, nor to disable them so that the size will not increase back.
There is a way to view them or download them, but not to remove or disable.
For other types of db engines, like MySQL, AWS does provide a way to remove them, by calling the rotation procedure twice in a row. Is there a similar way for SQL Server engines?
We have a large number of client databases with the same schema and does anyone knows how to create duplicates (like snapshot in SQL Server CE) from a provisioned client database, where the duplicates also can be synchronized with the server, since it takes really a long time to provision each client separately.
Thank you.
Create a backup of an existing provisioned database, restore on client, run PerformPostRestoreFixup before you sync the restored database for the first time.
I have SQL Server 2008 that houses a critical database for an enterprise application. There are also many other read-only apps that do read-only queries and I want these to hit a copy of the main database so it does not affect operations on the main database.
What is the best way to archive this? (Mirror, Log-Shipping, etc...)
Other notes
A latency of a few minutes on the second server would be fine.
There is about 7 applications that do short to long read-only queries.
Second database can be on a second server.
Having the ability to use the secondary database as a disaster backup might be nice.
The queries from these applications can happen at any time (they are not scheduled)
The main application would access the primary database (read/write)
Upgrading to SQL Server 2012/2014 is not an option at this time.
Would like to keep the performance hit to the primary server down if possible
What is the fastest way to backup/restore Azure SQL database?
The background: We have the database with size ~40 GB and restoring it from the .bacbac file (~4GB of compressed data) in the native way by Azure SQL Database Import/Export Service takes up to 6-8 hours. Creating .bacpac is also very long and takes ~2 hours.
UPD:
UPD.
Creating the database (by the way transactional consistent) copy using CREATE DATABASE [DBBackup] AS COPY OF [DB] takes only 15 minutes with 40 GB database and the restore is simple database rename.
UPD. Dec, 2014. Let me share with you our experience about the fastest way of DB migration schema we ended up with.
First of all, the approach with data-tier application (.bacpac) turned out to be not viable for us after DB became slightly bigger and it also will not work for you if you have at least one non-clustered index with total size > 2 GB until you disable non-clustered indexes before export - it's due to Azure SQL transaction log limit.
We stick to Azure Migration Wizard that for data transfer just runs BCP for each table (parameters of BCP are configurable) and it's ~20% faster than approach with .bacpac.
Here are some pitfalls we encountered with the Migration Wizard:
We run into encoding troubles for non-Unicode strings. Make sure
that BCP import and export runs with same collation. It's -C ... configuration switch, you can find parameters with which BCP calling
in .config file for MW application.
Take into account that MW (at least the version that is actual at the moment of this writing) runs BCP with parameters that will leave the constraints in non-trusted state, so do not forget to check all non-trusted constraints after BCP import.
If your database is 40GB it's long past time to consider having a redundant Database server that's ready to go as soon as the main becomes faulty.
You should have a second server running alongside the main DB server that has no actual routines except to sync with the main server on an hourly/daily basis (depending on how often your data changes, and how long it takes to run this process). You can also consider creating backups from this database server, instead of the main one.
If your main DB server goes down - for whatever reason - you can change the host address in your application to the backup database, and spend the 8 hours debugging your other server, instead of twiddling your thumbs waiting for the Azure Portal to do its thing while your clients complain.
Your database shouldn't be taking 6-8 hours to restore from backup though. If you are including upload/download time in that estimate, then you should consider storing your data in the Azure datacenter, as well as locally.
For more info see this article on Business Continuity on MSDN:
http://msdn.microsoft.com/en-us/library/windowsazure/hh852669.aspx
You'll want to specifically look at the Database Copies section, but the article is worth reading in full if your DB is so large.
Azure now supports Point in time restore / Geo restore and GeoDR features. You can use the combination of these to have quick backup / restore. PiTR and Geo restore comes with no additional cost while you have to pay for
Geo replica
There are multiple ways to do backup, restore and copy jobs on Azure.
Point in time restore.
Azure Service takes full backups, multiple differential backups and t-log backups every 5 minutes.
Geo Restore
same as Point in time restore. Only difference is that it picks up a redundant copy from a different blob storage stored in a different region.
Geo-Replication
Same as SQL Availability Groups. 4 Replicas Async with read capabilities. Select a region to become a hot standby.
More on Microsoft Site here. Blog here.
Azure SQL Database already has these local replicas that Liam is referring to. You can find more details on these three local replicas here http://social.technet.microsoft.com/wiki/contents/articles/1695.inside-windows-azure-sql-database.aspx#High_Availability_with_SQL_Azure
Also, SQL Database recently introduced new service tiers that include new point-in-time-restore. Full details at http://msdn.microsoft.com/en-us/library/azure/hh852669.aspx
Key is to use right data management strategy as well that helps solve your objective. Wrong architecture and approach to put everything on cloud can prove disastrous... here's more to it to read - http://archdipesh.blogspot.com/2014/03/windows-azure-data-strategies-and.html