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)
SharePoint
Score 7.6 out of 10
N/A
Microsoft's SharePoint is an Intranet solution that enables users to share and manage content, knowledge, and applications to empower teamwork, quickly find information, and collaborate across the organization.
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.
SharePoint Document Management excels as a central repository for storing, organising, and retrieving documents. It supports version control, metadata tagging, secure access, and integration with tools like Power Automate. At our organisation, it's used for managing contracts, policies, and supplier documents. SharePoint Workflow Automation integrates with Power Automate to streamline approvals, gather feedback, and automate recurring tasks. This reduces reliance on email chains and manual trackers.
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
Windows Explorer users have some difficulty having to constantly UPLOAD / DOWNLOAD files. Specifically on the DOWNLOAD when they are used to Drag & Drop in & out of LOCAL folders via Window's explorer.
Microsoft SharePoint supports multiple "library" types. When implementing our "image" library the search function is done via "tags" and boolean logic. This is challenging to most end users. I'd like our users to be able to search our Microsoft SharePoint image library without having to enter KEYWORD or other BOOLEAN logic.
Microsoft SharePoint can also be an internal website for each department or company wide communication tool but I believe these features are geared for much larger organizations. Since we are a SMB we really aren't using these features. So maybe something more useful to SMBs would be nice.
It's integral to our business. It's already included with most of the Office 365 licensing we buy, so the cost is effectively zero. It stores our files, it is the foundation for custom applications, and Microsoft only continues to enhance its functionality and its connections to other Microsoft tools. SharePoint just keeps getting better and better.
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.
No usability issues reported. Individual teams also have allocated areas which replace legacy shared drives on local LANs. Access to Sharepoint resources is fully integrated with corporate Active Directory with additional two-factor authentication required for administrative users. Users have access to Microsoft Services Hub which allows you to create, manage, and track support requests while staying current on Microsoft technologies with access to select self-paced learning paths
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.
The face to face training I received was on SharePoint Administration. It was rushed as there was a lot of information to cover and the application of the labs weren't that great either. I like to be able to relate what I am learning to what I am currently doing.
I like to learn at my own pace and online training allows for that. Additionally, you can skip through pieces of content that you already know or are already comfortable with. Microsoft actually offers great videos on their website for basic fundamental SharePoint Training. I have used these training videos in some of my own training sessions with end users.
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.
The reasons for selecting MS SharePoint are: SharePoint provides ease of use and web design assistance and support SharePoint helps you schedule your content for publishing. enables users to share documents with external parties and offers a better internal structure of the content and better indexing and searching capabilities.
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
