Apache Hadoop and Microsoft Azure Synapse Analytics are major players in the data management and analytics domain. User feedback suggests that Microsoft Azure Synapse Analytics holds an edge in feature richness, while Apache Hadoop is preferred for its open-source affordability.
Features: Apache Hadoop provides a distributed file system with high throughput and scalability, ideal for managing diverse data types including video and machine-generated data. Its HDFS is highly valued for cost-effective large data set storage. In contrast, Microsoft Azure Synapse Analytics excels in integration with Power BI, robust analytics, and data warehousing capabilities, offering scalability and user-friendly analytics functions.
Room for Improvement: Apache Hadoop needs advancements in memory handling and more intuitive visualization tools. The platform's open-source nature can complicate support and integration. Microsoft Azure Synapse Analytics users have expressed concerns about pricing models, initial setup challenges, and a need for improved machine learning functionalities and support documentation.
Ease of Deployment and Customer Service: Apache Hadoop, often an on-premises solution, can be difficult to deploy and relies on community-driven support, requiring substantial expertise. Meanwhile, Microsoft Azure Synapse Analytics is primarily cloud-based, offering smooth Microsoft tool integration. However, non-technical users may find deployment challenging, and there's a call for enhanced customer service.
Pricing and ROI: Apache Hadoop's cost-effectiveness is appealing, with no licensing fees due to its open-source nature, making it especially attractive for handling large data volumes. Microsoft Azure Synapse Analytics, with its pay-as-you-go model, provides scalability but involves potentially high costs, which may deter smaller businesses despite its optimized resource usage.
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.
It's not structured support, which is why we don't use purely open-source projects without additional structured support.
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.
It is a distributed file system and scales reasonably well as long as it is given sufficient resources.
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.
Continuous management in the way of upgrades and technical management is necessary to ensure that it remains effective.
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 problem with Apache Hadoop arose when the guys that originally set it up left the firm, and the group that later owned it didn't have enough technical resources to properly maintain it.
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 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.
If you don't do the upgrades, the platform ages out, and that's what happened to the Hadoop content.
I assess Apache Hadoop's fault tolerance during hardware failures positively since we have hardware failover, which works without problems.
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.
| Company Size | Count |
|---|---|
| Small Business | 14 |
| Midsize Enterprise | 8 |
| Large Enterprise | 21 |
| Company Size | Count |
|---|---|
| Small Business | 29 |
| Midsize Enterprise | 18 |
| Large Enterprise | 56 |
Microsoft Azure Synapse Analytics is an end-to-end analytics solution that successfully combines analytical services to merge big data analytics and enterprise data warehouses into a single unified platform. The solution can run intelligent distributed queries among nodes, and provides the ability to query both relational and non-relational data.
Microsoft Azure Synapse Analytics is built with these 4 components:
Microsoft Azure Synapse Analytics Features
Microsoft Azure Synapse Analytics has many valuable key features, including:
Microsoft Azure Synapse Analytics Benefits
Some of the benefits of using Microsoft Azure Synapse Analytics include:
Reviews from Real Users
Below are some reviews and helpful feedback written by Microsoft Azure Synapse Analytics users who are currently using the solution.
PeerSpot user Jael S., who is an Information Architect at Systems Analysis & Design Engineering, comments on her experience using the product, saying that it is “Scalable, intuitive, facilitates compliance and keeps your data secure”. She also says "We also like governance. It looks at what the requirements are for the company to identify the best way to ensure compliance is met when you move to the cloud."
Michel T., CHTO at Timp-iT, mentions that "the features most valuable are the simplicity, how easy it is to create a dashboard from different information systems."
A Senior Teradata Consultant at a tech services company says, "Microsoft provides both the platform and the data center, so you don't have to look for a cloud vendor. It saves you from having to deal with two vendors for the same task."
We monitor all Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
