Microsoft offers the Azure Logic Apps as a cloud-based integration service, supporting data and application integration.
$0
per execution
Azure Synapse Analytics
Score 7.7 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 Logic Apps
Azure Synapse Analytics
Editions & Modules
Actions
$0.000025
per execution
Standard Connector
$0.000025
per execution
Enterprise Connector
$0.001
per execution
Integration Account - Basic
$0.42
per hour
Integration Account - Standard
$1.37
per hour
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 Logic Apps
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
—
—
More Pricing Information
Community Pulse
Azure Logic Apps
Azure Synapse Analytics
Features
Azure Logic Apps
Azure Synapse Analytics
Cloud Data Integration
Comparison of Cloud Data Integration features of Product A and Product B
Microsoft Azure Logic Apps was a perfect solution for us to integrate the apps and products we used in our business to create automated workflows which were also complex and very advanced. This was a very new feature for us, and also it reduced our software costs massively and also saved us a lot of time. With the crisis, we were in back then Azure turned out to be the best cost-friendly solution because we only had to pay for what we used!
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.
Microsoft Azure should be unclouded with its pricing. We don't always know how much an inclusion will affect the monthly price. So we have to speculate where we are with the price and if we can afford to include another asset.
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 found them easy to use and adapt to different scenarios, from Azure management to link processes between REST APIs. Together with Function Apps, they're probably the most useful resource type for Azure. Today, I use them in production, and that's a key component: stable, secure, easy to manage, and maintain.
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.
Azure Logic Apps are backed by Azure and Microsoft. There is a wealth of information on the internet about both of these platforms. In addition to this Microsoft has a huge bush to using this platform and have offered many solutions and support options to the user. The only drawback is that it is a fairly new platform so the 3rd party information tends to be lacking.
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.
This is very dependent on the line of work you are in and the unique company requirements, as is the case with everything. We utilize Azure Logic Apps for all of our computing solutions within our domain, and it has always worked flawlessly. One of the simplest clouds to set up and use is by far the most popular.
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.
Moving to Serverless Computing obviously makes the organization get rid of dependent Infra.
ROI can be seen immediately as the required infra can be decommissioned after a successful quarter run.
Being deployed as a single entity or single app on Azure Logic Apps, Organizations need to be more careful with controls applied to meet compliance and security posture.
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