Azure Data Lake Storage Gen2 is a highly scalable and cost-effective data lake solution for big data analytics. It combines the power of a high-performance file system with massive scale and economy to help you speed your time to insight. Data Lake Storage Gen2 extends Azure Blob Storage capabilities and is optimized for analytics workloads.
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Azure SQL Database
Score 8.3 out of 10
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Azure SQL Database is Microsoft's relational database as a service (DBaaS).
We have used both Hadoop and GCS buckets for our storage needs of very large healthcare data. In terms of comparison with the Hadoop distributed Files system, Azure Data Lake Storage always stands in a far better position due to easy integration with various latest and widely …
Azure Data Lake Storage from a functionality perspective is a much easier solution to work with. It's implementation from Amazon EMR went smooth, and continued usage is definitely better. However, Amazon EMR was significantly cheaper overall between the high transaction fees …
We chose Azure Data Lake due to the fact that it was already a product under the Azure application suite. We didn't have to focus on integrating another 3rd party application within our environment. Also due to the fact Azure Data Lake scales its storage pools very efficiently, …
We decided long ago to develop for the Azure platform, so we only evaluate products from within Azure. And Azure Data Lake Storage is really the dominant offering within its space. But to give you a comparison, previously we used to use Azure SQL Database for our analytical …
Microsoft solutions provide great harmony in end-to-end data value creation, and Azure Data Lake Storage is highly compatible with other analytical solutions, e.g., Azure Data Factory and Databricks. So I would say that it is at the heart of the analytical solution in the …
AWS charges you on an hourly basis but Azure has a pricing model of per minute charge. In terms of short term subscriptions, Azure has more flexibility but it is more expensive. Azure has a much better hybrid cloud support in comparison with AWS. AWS provides direct connections …
I am much more familiar with Snowflake. I thought it was fairly straightforward to use and did not have to learn much syntax. With Azure Data Lake Storage, I have had to learn some new syntax and thought there was a steeper learning curve. We selected it because of cost savings.
We looked at the Amazon solution and it did not play as well with our existing tools and added a layer of maintenance that we were not willing to take on at the time. We thought that our Microsoft contract and support were good and that our internal team had the knowledge to …
The Azure Data Lake solution is designed for organizations that want to take advantage of big data. It provides a data platform that can help developers, data scientists, and analysts store data of any size and format and perform all types of processing and analytics across …
Better and more useful automation tools are available. Better at scaling and hosting your data. Greater security around access of data and encrypting where required. Allows for seamless integration in other Azure solutions which allows for greater flexibility when using the …
Depending on the use case they stack up very well. Google and AWS are well suited multi-cloud strategies or those that need a high level of RDS performance.
Mainly response time. Azure SQL Database is very fast and very reliable when it comes to executing queries and gathering the data results. Also, the exporting options it gives are far exceeding expectations and enable users to accommodate any deliverable in a timely and …
I selected Azure SQL because it integrates nicely with the technology stacks we currently maintain. The pricing is right, and clients are happy with that. Scaling is easy. Most of our clients don't want to maintain a full-blown database server, and they don't need one. For …
The simplicity and great features and good support of Microsoft as well as the more reasonable flexible price than other competitors is one of the important reasons for choosing it.
Oracle database is "the" serious database. There really is no competition in that field. SQL Database would be a serious competitor through the ease of implementation and the "no maintenance," but since it's too expensive for "normal" use (medium to small applications), it just …
It is very easy to setup SQL database on Azure. one can always refer to their documentation for best practices. It is highly available and scalable. It is cheaper than its alternatives and provide better performance than others. As we are using many other services of Azure for …
Director, eCommerce Analytics and Digital Marketing
Chose Azure SQL Database
The Azure SQL Database, compared to our on premise SQL server installation, is much easier to use in terms of seeing database diagnostics. There is a whole visualization platform that comes with the tool that will allow your database administrator to see what jobs are tying up …
Amazon's RDS offering is actually very good and is used in other parts of the company, we just have a lot of Azure experience so wanted to leverage that.
Being able to manage our databases in the cloud, scale quickly, and only require access to VMs made choosing Azure a no-brainer over a traditional SQL Server installation/integration. We don't have the budget or resources to integrate and maintain servers on our own, so using …
I would say MySQL in either Aurora or MariaDB form come close however, Azure SQL Database has a more streamlined approach to delivering a consistent programmability model, supported drivers and feature set.
Azure SQL Database T-SQL is advantageous and more complete than SQL …
Azure owned by Microsoft who owned SQL Server, so provided a variety of tools for easy migration/transition and from on-premises to the cloud; and management. I recommend using Azure for any on-prem SQL server databases.
Azure SQL is a clear upgrade to SQL Server 2012 and pretty much has the advantage with all the extra features that it has. Security, queries, exporting tables, T-SQL has all improved. Transitioning 18+ years of an in-house database to the cloud was a struggle, but for the …
We moved away from Oracle and NoSQL because we had been so reliant on them for the last 25 years, the pricing was too much and we were looking for a way to cut the cord. Snowflake is just too up in the air, feels like it is soon to be just another line item to add to your Azure …
Amazon Relational Database Service is the other obvious competitor. We were already in Azure, so it's not a serious contender for our business due to that bias already, but I do personally find the marketing and documentation of RDS more intimidating to sort through.
Comparing with Amazon Aurora: Azure SQL DB is 100% compatible with SQL Server and Aurora is compatible with MySQL and PostGreSQL. Because of if, SQL DB suits large enterprises with hundreds of databases better. Comparing with Oracle: the main issue is that Oracle will try to …
It stacks up in different ways, for the most part, I think Microsoft is doing a really good job versus the competition. They basically started database type products from the beginning. I've always been excited about updates and can see their progress over time. Get's me really …
Azure Data Lake storage is well suited for applications/use cases within organizations where capturing and storing large amounts of data in any format is required, primarily for storing and processing purposes. It's an easy and cost-effective cloud solution for your application data. The ability to integrate with other Azure Services like Azure Databricks and Azure Data Factory is superb.
Your upcoming app can be built faster on a fully managed SQL database and can be moved into Azure with a few to no application code changes. Flexible and responsive server less computing and Hyperscale storage can cope with your changing requirements and one of the main benefits is the reduction in costs, which is noticeable.
Azure Data Lake Storage is extremely scalable. It allows us to scale up or down endlessly based on what we need including replication.
In terms of security, Azure Data Lake Storage fits our requirements really well as we can monitor and encrypt seamlessly. We can also assign permissions through roles and grant network-level access.
Due to the fact that it can scale, we are able to monitor the cost of storage and any given time and make financial decisions about our infrastructure based on how small or big we want to scale.
Scalability is #1: if it used to be an almost no-win endeavour to try to modernize your server or migrate to other hardware, with Azure SQL Database it becomes a press of a button.
All the tools simply work after you are on Azure SQL Database.
The applications do not need changes in order to start using Azure SQL Database.
Hybrid Cloud scenarios will work.
Clustering and failover - already there.
You can start monitoring the use and extract performance insights in a new way in Azure.
I'd like to see a better cross-platform native client. Azure Data Explorer is fine, but it's far from the "SSMS" kind of experience SQL Server users are used to.
Listing a large number of file is somewhat problematic and slow. Using the native C# library, running directly on an Azure VM, it can take several hours to list just a couple million files.
Switching from V1 to V2 requires the creation of a new Storage Account and that's pretty inconvenient.
A little slow on processing complex or large Views. We use a lot of Views to feed our BI system, and the processing time could see some improvement, IMHO.
Additional monitoring components would be nice too, automating some built in performance measurement tools would be a nice feature.
Price can always be improved as well. It’s not bad, but room for improvement.
The interfaces are intuitive once you are familiar with all the functions. The ability to use different tools to interact with the platform, such as directly via a browser or code editors such as VS Code or Visual Studio is a great option and allows for integrating withn the project and other testing and developing tools.
We give the support a high rating simply because every time we've had issues or questions, representatives were in contact with us quickly. Without fail, our issues/questions were handled in a timely matter. That kind of response is integral when client data integrity and availability is in question. There is also a wealth of documentation for resolving issues on your own.
The Azure Data Lake solution is designed for organizations that want to take advantage of big data. It provides a data platform that can help developers, data scientists, and analysts store data of any size and format and perform all types of processing and analytics across multiple platforms and programming languages. It can work with your existing solutions, such as identity management and security solutions. It also integrates with other data warehouses and cloud environments. It can be useful for organizations that need the above softwares.
I selected Azure SQL because it integrates nicely with the technology stacks we currently maintain. The pricing is right, and clients are happy with that. Scaling is easy. Most of our clients don't want to maintain a full-blown database server, and they don't need one. For them, Azure SQL is the right size.
The cost can be high for more advanced work. In some cases, for instance, time limits and lab runtimes may be too short if you are too slow to learn what is explained as you go along.
promote flexible team communication. You can create different spaces for different teams, and share files and tasks.