I wonder to know how data is stored on disk in Azure Table? are they stored in a columnar format like HBase?
Microsoft Azure Table is a form of Microsoft Azure Storage, a scalable cloud storage system. There are three layers within an Azure Storage stamp and Stream layer stores the bits on disk, and in charge of distributing and replicating the data across many servers to keep the data durable within a stamp. Please see “Stream Layer” section in the following paper (http://sigops.org/sosp/sosp11/current/2011-Cascais/11-calder-online.pdf) to understand how we manage data on the hardware.
I can't say for sure, but I don't think so. Azure Table Storage is a key-value store. HDInsight is Azure's column-family storage, built on Hadoop, similar to HBase.
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We have a requirement to move data from oracle Cloud storage to Azure Cloud storage.
The requirement is basically to move data from an Oracle ADW database (hosted on Oracle cloud) to Snowflake database (hosted on Azure).
Since the data volume in tables is huge (some with 60mil+ records) we do not wish to use any ETL tool and instead want to setup a pipeline as below.
Oracle ADW database -> Store data in Oracle storage --> Move data to Azure Cloud storage -> Load into Snowflake using snowpipe or similar snowflake utilities.
How should I go about this implementation?
Also share your views on whether we can use Oracle fastconnect and Azure ExpressRoute to directly pull data from Oracle Cloud onto snowflake (or into Azure storage)
I am looking for the same thing with the simplest method from Oracle (on prem but could be cloud), into Snowflake. Looks like data must be exporeted or dropped to external tables, shifted to Azure Blob storage (like AWS S3), then pushed into Snowflake using COPY INTO - basically copying on disk external tables. This is what Snowpipe does:
"Snowpipe copies the files into a queue, from which they are loaded into the target table in a continuous, serverless fashion based on parameters defined in a specified pipe object. The following table indicates the cloud storage service support for automated Snowpipe from Snowflake accounts hosted on each cloud platform:"
It's been a while since I have worked with this. The other option is GoldenGate, which was not expensive the last time I looked into it:
https://www.snowflake.com/blog/continuous-data-replication-into-snowflake-with-oracle-goldengate/
Easy, simple, fast. Anyone have any better ideas would be appreciated.
I am currently in the process of building a SQL database in Microsoft Azure for handling pictures, documents, etc. What is the most efficient/best way of storing data? Uploading the files directly to the DB, or by sourcing the files from something like Azure BLOB? I have read numerous posts about people uploading it directly to the DB, but I am concerned about its efficiency.
Thank you in advance for any replies.
You can store in something like Azure SQL DB for example but I would not recommend it, you should definitely store in Azure Storage (BLOB) and then for reference store in a DB. Azure has multiple relational and NoSQL data stores which are offered as platform services.
I would do two things, use a NoSQL platform data store like Cosmos DB using SQL Core API to store the metadata for the images, here you can use the filename as the partition ID to do a point read (this is very fast read and it would be a very cheap option with blazing fast performance) and secondly I would use Azure CDN to make sure images are accessed via CDN so that they are faster.
Azure CDN has three options; Akamai, Verizon and Microsoft. You can test which CDN is faster from where you are from here: https://cloudharmony.com/speedtest-for-azure
Using the above URL you can also use to test which Azure region is closer to you so to use that region, or test for your end-users and choose the region closer tot them.
I would say storing in Azure BLOBs is a better idea. Imagine you have 100 GB files stored in DB.
It will slow down your query if your table is not designed properly.
Backup & Restore DB will be very slow.
Azure DB is more expensive than Azure BLOB for the same size.
If your total file size is small enough, it doesn't make much difference.
I am using BigQueryIO to publish data into BigQuery from a Google Dataflow job.
AFAIK, BigQuery can be used to query data from Google Cloud Storage, Google Drive and Google Sheets.
But when we store data using BigQueryIO, where the data will stored? Is it in Google Cloud Storage?
Short answer - BigQueryIO Write/Read to/from BigQuery Table
To go a little deeper:
BigQuery stores data in the Capacitor columnar data format, and offers the standard database concepts of tables, partitions, columns, and rows.
It manages the technical aspects of storing your structured data, including compression, encryption, replication, performance tuning, and scaling.
You can read more about BigQuery different components in BigQuery Overview
Cloud Storage is a separate service from Big Query. Internally, Big Query manages its own storage.
So, if you save your data to Cloud Storage, and then use the bq command to load a Big Query table from a file in Cloud Storage, there are now 2 copies of the data.
Consequences include:
If you delete the Cloud Storage copy, the data will still be in Big Query.
Fees include a price for each copy. I think in April 2017 long term storage in BQ is around $0.01/GB, and in cloud storage around $0.01-$0.026/GB depending on storage class.
If the same data is in both GCS and BQ, you are paying twice. Whether it is worthwhile to have a backup copy of data is up to you.
BigQuery is a managed data warehouse, simply say it's a database.
So your data will be stored in BigQuery, and you can acccess it by using SQL queries.
I want to copy data from sharepoint to microsoft azure sql DW using azure datafactory or alternative service. Can I do this. Please anyone help me with this.
You can do this by setting up a data pipeline using Azure Data Factory to Azure blob storage. Afterwards you can use Azure's fast PolyBase technology to load the data from blob to your SQL Data Warehouse instance.
Can I ask how much data you intend on loading into the DW? Azure Data Warehouse is intended for use with at least terabyte level data up to petabyte compute and storage. I only ask because each SharePoint list or Excel file has a maximum of 2GB per file.
I have the following set up:
Azure service
Azure SQL database
Azure Table Storage
Azure Blob Storage
I am trying to develop a backup strategy for this service.
The thing is, that SQL, Tables and BLOBs should be synced. In the backup all three of those have to be of the same version. (backups taken at the same moment). And the main problem is - I can only afford several minutes downtime, not more than that.
What should I do? May be there is existing solution?
Windows Azure Storage supports geo-replication for Blobs, Tables and Queues. Data in the storage account is made durable by replicating transactions across different storage nodes in the same region (LRS) or a secondary region (GRS). GRS is the default redundancy option when creating a storage account. Refer to http://blogs.msdn.com/b/windowsazurestorage/archive/2013/12/11/introducing-read-access-geo-replicated-storage-ra-grs-for-windows-azure-storage.aspx for more details.
If you want to build a custom backup solution then you could use the techniques suggested in the below 2 blogs
1) http://blogs.msdn.com/b/windowsazurestorage/archive/2010/04/30/protecting-your-blobs-against-application-errors.aspx
2) http://blogs.msdn.com/b/windowsazurestorage/archive/2010/05/03/protecting-your-tables-against-application-errors.aspx
I am not sure of the exact use case of why you need to backup azure table and blob. You can backup All the above services without downtime; might be there would be slight glitch or bottleneck performance with SQL database durning back.
The single shot answer is to write a custom script which would read the data from azure table ( or SQL database, or the required service ) make a archive (packaging) and store it back.
The important thing to note here is where would storage backups, broadly speaking generally store the archives in blob. In this case you have thing where you would be storing, if you are storing on-premises you need calculate upon the storage locally, out bandwidth cost and latency of the data transfer from azure.
PS : cloud storage by itself has good leave of availability and durability, you further improve these factors by enabling geo-replication