The Microsoft Azure App Service is a PaaS that enables users to build, deploy, and scale web apps and APIs, a fully managed service with built-in infrastructure maintenance, security patching, and scaling. Includes Azure Web Apps, Azure Mobile Apps, Azure API Apps, allowing developers to use popular frameworks including .NET, .NET Core, Java, Node.js, Python, PHP, and Ruby.
$9.49
per month
Azure Synapse Analytics
Score 7.6 out of 10
N/A
Azure Synapse Analytics is described as the former Azure SQL Data Warehouse, evolved, and as a limitless analytics service that brings together enterprise data warehousing and Big Data analytics. It gives users the freedom to query data using either serverless or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.
$4,700
per month 5000 Synapse Commit Units (SCUs)
Pricing
Azure App Service
Azure Synapse Analytics
Editions & Modules
Shared Environment for dev/test
$9.49
per month
Basic Dedicated environment for dev/test
$54.75
per month
Standard Run production workloads
$73
per month
Premium Enhanced performance and scale
$146
per month
Tier 1
$4,700
per month 5,000 Synapse Commit Units (SCUs)
Tier 2
$9,200
per month 10,000 Synapse Commit Units (SCUs)
Tier 3
$21,360
per month 24,000 Synapse Commit Units (SCUs)
Tier 4
$50,400
per month 60,000 Synapse Commit Units (SCUs)
Tier 5
$117,000
per month 150,000 Synapse Commit Units (SCUs)
Tier 6
$259,200
per month 360,000 Synapse Commit Units (SCUs)
Offerings
Pricing Offerings
Azure App Service
Azure Synapse Analytics
Free Trial
Yes
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
Free and Shared (preview) plans are ideal for testing applications in a managed Azure environment. Basic, Standard and Premium plans are for production workloads and run on dedicated Virtual Machine instances. Each instance can support multiple applications and domains.
—
More Pricing Information
Community Pulse
Azure App Service
Azure Synapse Analytics
Features
Azure App Service
Azure Synapse Analytics
Platform-as-a-Service
Comparison of Platform-as-a-Service features of Product A and Product B
You may easily deploy your apps to Azure App Service if they were written in Visual Studio IDE (typically.NET applications). With a few clicks of the mouse, you may already deploy your application to a remote server using the Visual Studio IDE. As a result of the portal's bulk and complexity, I propose Heroku for less-experienced developers.
It's well suited for large, fastly growing, and frequently changing data warehouses (e.g., in startups). It's also suited for companies that want a single, relatively easy-to-use, centralized cloud service for all their data needs. Larger, more structured organizations could still benefit from this service by using Synapse Dedicated SQL Pools, knowing that costs will be much higher than other solutions. I think this product is not suited for smaller, simpler workloads (where an Azure SQL Database and a Data Factory could be enough) or very large scenarios, where it may be better to build custom infrastructure.
Quick to return data. Queries in a SQL data warehouse architecture tend to return data much more quickly than a OLTP setup. Especially with columnar indexes.
Ability to manage extremely large SQL tables. Our databases contain billions of records. This would be unwieldy without a proper SQL datawarehouse
Backup and replication. Because we're already using SQL, moving the data to a datawarehouse makes it easier to manage as our users are already familiar with SQL.
With Azure, it's always the same issue, too many moving parts doing similar things with no specialisation. ADF, Fabric Data Factory and Synapse pipeline serve the same purpose. Same goes for Fabric Warehouse and Synapse SQL pools.
Could do better with serverless workloads considering the competition from databricks and its own fabric warehouse
Synapse pipelines is a replica of Azure Data Factory with no tight integration with Synapse and to a surprise, with missing features from ADF. Integration of warehouse can be improved with in environment ETl tools
I enjoy the fact that Azure App Service can be managed by the Azure portal and a fully graphical user interface, as well as from two different flavors of command-line interface, i.e. Azure CLI and Azure Powershell. By utilizing the Azure Cloud Shell, we are able to switch between Azure Bash (CLI) and Powershell at any given moment and manage the Azure App Service settings from devices of any form-factor (Web based management).
The data warehouse portion is very much like old style on-prem SQL server, so most SQL skills one has mastered carry over easily. Azure Data Factory has an easy drag and drop system which allows quick building of pipelines with minimal coding. The Spark portion is the only really complex portion, but if there's an in-house python expert, then the Spark portion is also quiet useable.
We had an issue where we deployed too large of a resource and didn't notice until the bill came through. They were very understanding and saw we weren't utilizing the resources so they issued a generous refund in about 4 hours. Very fast, friendly, and understanding support reps from my experience.
Microsoft does its best to support Synapse. More and more articles are being added to the documentation, providing more useful information on best utilizing its features. The examples provided work well for basic knowledge, but more complex examples should be added to further assist in discovering the vast abilities that the system has.
Azure has many data center, their services are more reliable. Azure has way more features than both Linode and DigitalOcean. If someone wants a complete reliable service, he/she must go to Azure instead of Linode and DigitalOcean because even though azure charges more, it is worth the money you pay there.
In comparing Azure Synapse to the Google BigQuery - the biggest highlight that I'd like to bring forward is Azure Synapse SQL leverages a scale-out architecture in order to distribute computational processing of data across multiple nodes whereas Google BigQuery only takes into account computation and storage.
Licensing fees is replaced with Azure subscription fee. No big saving there
More visibility into the Azure usage and cost
It can be used a hot storage and old data can be archived to data lake. Real time data integration is possible via external tables and Microsoft Power BI