Azure Synapse Analytics Reviews and Ratings

Use Cases and Deployment Scope

We usually deal with large scale data migrations. Synapse, at times, fits in perfectly with a fabric lakehouse-warehouse solution or a standard data warehousing solution bringing and collating data from multiple data sources into a data arehouse in the form of Synapse. While there are multiple trends in the data space involving lakehouses and delta lake and what not, Synapse still holds its place best when warehouses are talked about. With flexibility of external tables and serverless workloads for faster data reads, to the scalability of database tables with transactional and analytical use cases, Synapse can serve a wide array of use cases and rightfully so.

Likelihood to Recommend

Usually, there is a huge overlap between use cases that suit Synapse also suiting databricks, Fabric Warehouse etc. However, the best suited use cases for Synapse or those involving mostly ELT and data warehousing. For example, If you have data lying around in isolated databases, data that is clean but perhaps not curated, would serve as a perfect use case for Synapse to jump in and have the best suited solution. You could use a plethora of Synapse Pipelines' connectors to simply extract the data from these isolated Databases, load it into staging tables, apply basic refinement to push it into dbo tables and perform analytics on top of this. With intuitive UI and powerful dynamic expression, it's an accelerated metadata driven framework knocking at your door waiting to happen with just a few drag and drops and some metadata table magic.

Use Cases and Deployment Scope

We use it as a primary driver of our DWH solution. We use the spark cluster to process a very large amount of data on a daily schedule. Using Synapse notebooks has enabled us to reuse a single notebook for historization of the data across multiple sources. All of the sources that land in our S3 bucket(either via push or pull mechanism) we are able to clean, store and transform using Synapse notebooks.

Likelihood to Recommend

<div>If you're looking for a spark based platform that integrates well with the rest of the Azure stack, Synapse is a really good choice.</div><div>

</div><div>Its a really good for batch loading of massive datasets. (Think SAP ACDOCA and similar).</div><div>

</div><div>Its less appropriate if you need to ingest via streaming. There aren't a lot of options for streaming or API data to be handled.</div>

Use Cases and Deployment Scope

In my organization , Azure Synapse Analytics plays a vital role cause it really helps in data integration, transformation and reporting process.

It serves the foundation of our enterprise data ware house from multiple sources including Salesforce , Pardot , HubSpot, Share point and our internal data base etc.

It really helps to consume less time to make reports on Power BI

Likelihood to Recommend

It basically handle large data sets across multiple channels for different business units.

Example : we consolidate lead gen, campaign spend, sales pipeline etc.

It also create automated data flow that pulls from various sources like Salesforce , Excel , Pardot and SQL database. It also cleaning , transforming and sorting the data for Power BI dashboards without manual efforts.

Use Cases and Deployment Scope

Our data warehouse was growing at a 1TB/year rate, and we needed a solution that would be both cheap and effective.

Previously we were using Azure SQL Database with its JSON capabilities and various Azure serverless services to manage our data, but at that growth rate, time and cost were becoming limiting factors.

Likelihood to Recommend

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.

Use Cases and Deployment Scope

As a consulting company, we implement data warehouse solutions for our clients. We use Azure Synapse for enterprises data warehouse implementations. Data from various internal sources like sales, finance and operations are integrated into Synapse via Azure Data Factory and Data Lake. It’s used as reporting data source for Microsoft Power BI as well.

Likelihood to Recommend

Big Data load are made simple using polybase feature. You just have to create external tables to connect to any data source files (of any format) in Azure Data Lake. There is no need for map-reducing that is done in Hadoop clusters. You just need to know sql to do data integration.

Use Cases and Deployment Scope

We've been using Azure Synapse Analytics to create data pipelines for onPrem/onCloud ETL processing where the transform data will store inside the Azure Data Lake for further processing using PowerBI.

Likelihood to Recommend

In terms of a well-suited scenario - the Azure Synapse can be used to capture data from multiple sources (especially from onPrem sources apart from Dataverse) and update the transformed data based on the given conditions (eg: refresh data based on the specified date/time ranges). Also, the transformed data can simply be transferred to Azure Data Lake for further processing by utilizing other analytics tools such as PowerBI.

Use Cases and Deployment Scope

I am an independent developer using Azure Synapse for other companies. My company is machinery production oriented (i.e. automotive companies) so I'm used to [utilizing] the Synapse for statistics-driven quality control, some logistics stuff, etc.

Likelihood to Recommend

The most frequent answer to questions like this should be... IT DEPENDS. Synapse Analytics has some role in its DNA. It's not dedicated [to] tasks like some OLTP with many reads, however. When we are talking about Azure Synapse, we are talking about modernized BI stuff with great capabilities to involve big data processing to reach deeper insights [into] our data.

Use Cases and Deployment Scope

Azure Synapse Analytics is being used for data Warehousing - Azure Data Factory to pull in the initial data from source to Data Lake, then Spark notebook to process from raw (bronze) to staging (silver) in Synapse dedicated pools, then stored procedures in Synapse dedicated pool to process from staging to reporting (gold).

Likelihood to Recommend

Azure Synapse Analytics is well suited to Data Warehouse scenarios with large data tables because of its distributed computing. If most tables have fewer than 1 million rows, then the cost of Synapse is not worthwhile - regular Azure SQL or Azure Analysis Services could suffice. If most tables have more than 1 million rows, then it's worthwhile to get the additional speed for querying large data sets.

Use Cases and Deployment Scope

We use Azure Synapse Analytics (Azure SQL Data Warehouse) to hold all our daily sales data to serve reports. Without any storage constraint, we save large datasets and process them in a matter of time, thanks to the Azure lake storage support and Massive Parallel processing capabilities. It supports major file formats like Avro, Parquet and many more.

Likelihood to Recommend

Enterprises which require to manage huge datasets and need support to bigdata capabilities in a cost efficient way. Enterprises that process real-time data for their analysis like streaming data and IOT data. Combining Azure Synapse Analytics and Data lake storage provides a better performance and cost effective way to manage a huge dataset.

Use Cases and Deployment Scope

Microsoft Azure Synapse Analytics (formally Azure SQL Data Warehouse) is being used as our marketing data warehouse. We are pulling data down from a number of different API's such as Facebook ads, Google ads and Google analytics, and then pumping that information back into the Azure Synapse Analytics Warehouse on a daily basis.

Likelihood to Recommend

Azure Synapse Analytics is very well suited for companies that are using the Microsoft Power BI analytics tool (business intelligence). The reason being, you don't need to provide a data gateway to move data from your database to the reporting service online if you are using this type of database. This is a huge win for processing data.