Microsoft Azure Synapse Analytics and Azure Data Factory are advanced tools competing in data orchestration and analytics on the Microsoft Azure platform. Azure Synapse Analytics seems to have the upper hand in pricing flexibility due to its pay-as-you-go model, while Azure Data Factory offers more predictable cost management with its usage-based pricing.
Features: Azure Synapse Analytics is noted for its seamless integration with Power BI and Data Factory, excellent scalability, and reliable MPP architecture. It efficiently handles large data sets. Azure Data Factory stands out for its ETL capabilities, diverse connectors, and ease of data integration across multiple sources.
Room for Improvement: For Azure Synapse Analytics, improved governance tools, schema management, and enhanced external service integration are areas for development. Azure Data Factory could benefit from enhanced speed, better parallelization, and improved third-party system integration, especially with SAP.
Ease of Deployment and Customer Service: Both solutions offer flexible and scalable deployment in public cloud environments. Customer support is generally responsive, but Synapse users report mixed experiences, whereas Data Factory users find the support more consistent.
Pricing and ROI: Azure Synapse Analytics offers a pay-as-you-go pricing model, which can be less predictable but scalable for larger enterprises. In contrast, Azure Data Factory offers consumption-based pricing, which is more predictable for smaller setups but costs may rise with data processing demands. Both solutions offer integration benefits that enhance ROI through efficient data management.
Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness.
Some of my customers have indeed seen a return on investment with Microsoft Azure Synapse Analytics as they used it for analytics to drive decision-making, improving their processes or increasing revenue.
On a scale of one to ten, I would rate the technical support as nine.
The technical support from Microsoft is rated an eight out of ten.
The technical support is responsive and helpful
They are slow to respond and not very knowledgeable.
This is an underestimation of the real impact because we use big data also to monitor the network and the customer.
I would rate the support for Microsoft Azure Synapse Analytics as an eight out of ten.
Azure Data Factory is highly scalable.
I did not experience scalability issues.
Microsoft Azure Synapse Analytics is scalable, offering numerous opportunities for scalability.
For the scalability of Microsoft Azure Synapse Analytics, I would rate it a 10 until you remain in the Azure Cloud scalability framework.
Recovering from such scenarios becomes a bit problematic or time-consuming.
The solution has a high level of stability, roughly a nine out of ten.
It gives me the accurate result.
I have been using Azure Data Factory for a very long time, and I did not find too many issues.
Performance and stability are absolutely fine because Microsoft Azure Synapse Analytics is a PaaS service.
I find the service stable as I have not encountered many issues.
We have never integrated Microsoft Azure Synapse Analytics with Databricks, but we have mostly pulled data from on-premises systems into Azure Databricks.
The ability to handle the largest volumes of data is another concern; if I have to manage more than one terabyte of data every day, I am not comfortable dealing with Azure Data Factory and had to switch to Oracle Data Integrators (ODI) because it lacks performance features.
If I am making a pipeline, it should give me suggestions, such as which activity should be used, so that I don't have to remember each activity.
Incorporating more dedicated API sources to specific services like HubSpot CRM or Salesforce would be beneficial.
Microsoft Azure Synapse Analytics is an excellent product because it includes both SIEM and orchestration capabilities with playbooks.
There is a need for better documentation, particularly for customized tasks with Microsoft Azure Synapse Analytics.
Databricks is a very rich solution, with numerous open sources and capabilities in terms of extract, transform, load, database query, and so forth.
The pricing is cost-effective.
It is considered cost-effective.
The cheapest tier costs about $4,000 to $4,700 a year, while the most expensive tier can reach up to $300,000 a year.
I think the price of Microsoft Azure Synapse Analytics is very expensive, but that's not only for Microsoft Azure Synapse Analytics—it's for the cloud in general.
I find the pricing of Microsoft Azure Synapse Analytics reasonable.
It connects to different sources out-of-the-box, making integration much easier.
The platform excels in handling major datasets, particularly when working with Power BI for reporting purposes.
Regarding the integration feature in Azure Data Factory, the integration part is excellent; we have major source connectors, so we can integrate the data from different data sources and also perform basic transformation while transforming, which is a great feature in Azure Data Factory.
One of the most valuable features in Microsoft Azure Synapse Analytics is the ability to write your own ETL code using Azure Data Factory, which is a component within Synapse.
Microsoft Azure Synapse Analytics offers significant visibility, which helps us understand our usage more clearly.
For Microsoft Azure Synapse Analytics, the integration is the most valuable feature, meaning that whatever you need is fast and easy to use.
| Product | Mindshare (%) |
|---|---|
| Microsoft Azure Synapse Analytics | 6.1% |
| Azure Data Factory | 5.2% |
| Other | 88.7% |
| Company Size | Count |
|---|---|
| Small Business | 31 |
| Midsize Enterprise | 21 |
| Large Enterprise | 64 |
| Company Size | Count |
|---|---|
| Small Business | 28 |
| Midsize Enterprise | 18 |
| Large Enterprise | 60 |
Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.
Microsoft Azure Synapse Analytics integrates data warehousing and big data analytics seamlessly. It provides scalability and user-friendly features for efficient, real-time reporting and data management.
Azure Synapse Analytics is designed for seamless data integration, allowing users to scale their operations effectively while providing extensive analytics capabilities. It supports both traditional data warehousing and big data solutions with real-time reporting through an interactive interface that integrates well with Power BI. The platform's serverless flexibility optimizes cost while ensuring robust security, leveraging users' familiarity with SQL technologies. Scalability allows processing of large datasets efficiently, empowering companies to connect disparate data sources and support industry-specific needs. Despite its strengths, Synapse users often seek improved governance, schema management, and technical support. Enhanced integration with Microsoft and third-party tools, along with better data loading capabilities, are also desired.
What are the key features of Microsoft Azure Synapse Analytics?Azure Synapse Analytics is extensively implemented across sectors like healthcare, finance, marketing, and government. Organizations use it to build data pipelines, perform analytics modeling, and facilitate reporting. It supports data transformation, migration, and orchestration, enhancing business intelligence and decision-making capabilities by efficiently handling big data and connecting disparate data sources.
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