Azure Synapse Analytics

Score6.8 out of 10

52 Reviews and Ratings

What is Azure Synapse Analytics?

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.

Categories & Use Cases

Paras Jasal View profile

Data Engineer in Engineering at Celebal Technologies (1001-5000 employees employees)

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.

Pros

Data Warehousing
Data Engineering
Data Marts
Data Analytics

Cons

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

Return on Investment

Positive Impact: Lots of happy customers who did not want to go the full road of databricks and delta lake and wanted to maintain Data Warehouse consistency, something delta lake, at times still fails to deliver
Positive Impact: You don't need to be technically sound to understand the UI, a few drag and drops and you have a copy pipeline at your disposal. Empowers customers like no other
Negative Impact: With so many frequent introductions from Azure, which are nothing but differently named forks of the same thing. Case in point, Fabric Data Factory, Synapse pipelines and Azure Data Factory, leaves the customers confused and unsure of the direction ahead

Usability

Alternatives Considered

Microsoft Fabric, Amazon Redshift, Azure Databricks and Google BigQuery

Other Software Used

Azure Databricks, Microsoft Fabric, Azure Data Factory

Borna Marković View profile

Data Engineer in Information Technology at BDR (1001-5000 employees employees)

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.

Pros

Large batch load processing
Reusing notebooks across multiple sources
Accepting parameters sent from ADF(seamless integration)

Cons

Its not being actively developed, so no new features
It lags behind Databricks in features it provides
Synapse Orchestrator is not the best(Azure Synapse Pipelines)

Return on Investment

Migrating away from legacy database DWH(SQL Server, Oracle)
Incorporating Delta tables technology
Lower storage costs(Azure storage is cheaper than storing in a database)
Much faster processing time(from 12 hours loads to 5 hours)

Usability

Alternatives Considered

Azure Databricks and Microsoft Fabric

Other Software Used

Azure Data Factory, Azure Functions, Azure Database

Verified User

Analyst in Marketing (10,001+ employees employees)

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

Pros

Seamless Data fetching across multiple sources
Handle easily large data set on SQL Query
Deep Integration with Power BI for real time dashboards and reports

Cons

They have limited UI responsiveness and usability in Synapse Studio.
Limited custom visualization in synapse
Spark performance is inconsist.

Return on Investment

It really helps to action in less time
Really helps to track campaign ROI
Scalability for growing data needs

Usability

Alternatives Considered

Azure Data Factory, Google BigQuery and Snowflake

Other Software Used

Salesforce CRM Analytics, Bullhorn ATS & CRM, Draup for Sales

Scott Kennedy View profile

Director, eCommerce Analytics and Digital Marketing in Marketing at Franklin Sports (201-500 employees employees)

Pros

They unify many data sources easily
There is some "code free" ETL work it enables
There is some AI integration that works nice

Cons

The cost structure is difficult to understand
The job scheduling capabilities aren't easy to use
The logging metrics aren't easy to see

Most Important Features

Ability to remove dependency on data gateway
data processing speed
serverless maintainance

Return on Investment

Easy database management using modern tools
Easy integration with Power BI
Cloud-native HTAP

Alternatives Considered

Azure SQL Database and Snowflake

Other Software Used

Snowflake, Azure SQL Database, PostgreSQL

Vladimír Mužný View profile

Owner, Developer at DROPMAN s.r.o. (1-10 employees employees)

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.

Pros

The combination of SQL/unstructured data
Keeping things "complicated, but simple"; [heterogeneous] data formats seen as just SQL tables to business experts used to use Power BI, Excel, and any other traditional SQL-oriented BI tools
Integration options using "Synapse pipelines", the application of ADFs
The greatly integrated solution of independent things (Spark MPP cluster, MPP SQL Servers, ADFs) - all sitting under one roof. Great job!
Integration with super-fast, globally replicated data. I really appreciate the integration of NoSQL databases (namely Core API and Mongo API under Cosmos DB) with purely batch-processed BI data

Cons

I have no idea right now. But... Synapse Analytics are typically seen as batch-processing of source data. What about tighter cooperation with streaming features like Event Hubs?

Return on Investment

It's actually hard to answer the question as it is built up, sorry. But imagine, you are used to [sending] paper letters to your customers. What are your spending [on] the letters? You have some imagination, however, but let's develop a simple chart showing your spendings related to any other spendings, or, more descriptively, compared with expected profit. Oh, my! Is it really so much? What about some e-mail campaign next time? We can talk about dozens of similar examples, folks. Until data is seen in graphical format, it's just some opinion on what's going on in our businesses.
Using Synapse Analytics as well as any other cloud resource needs a big change to the administrator's mindset. Basically, the cloud is not just about technical skills like "I love the MPP approach of data processing", but it is about, says, economies of operations. Scaling stuff up and down, pausing servers, this is what the utilization of the cloud is all about! Go and mention it to people!