Apache Hadoop and Microsoft Azure Synapse Analytics are key players in the data analytics domain, offering robust capabilities for managing and processing large datasets. Microsoft Azure Synapse Analytics appears to have an advantage due to its strong integration with Power BI, high scalability, and a more cohesive ecosystem that enhances performance and flexibility.
Features: Apache Hadoop's HDFS enables efficient storage of various data types and supports large datasets, with distributed processing through tools like Spark. Its integration capabilities with other big data tools bolster its appeal for data-driven tasks. Conversely, Microsoft Azure Synapse Analytics offers seamless Power BI integration for advanced analytics, a dual-layer architecture that separates compute and storage for optimal performance, and a flexible, scalable setup allowing serverless options.
Room for Improvement: Apache Hadoop could enhance user-friendliness and integrated visualization capabilities, requiring better real-time data processing tools and performance optimizations. Microsoft Azure Synapse Analytics faces challenges in its complex initial setup and documentation, with suggestions for improved integration with Microsoft tools and better monitoring. Clearer cost models and cross-platform compatibility would further benefit Synapse.
Ease of Deployment and Customer Service: Apache Hadoop is mainly deployed on-premises, offering flexibility at the cost of significant setup and administrative effort. Its customer service relies heavily on community forums and support. Microsoft Azure Synapse Analytics operates primarily in the public cloud, benefiting from structured support through Microsoft's ecosystem, though user feedback about support experiences varies.
Pricing and ROI: Apache Hadoop is cost-effective due to its open-source model, attractive for budget-sensitive organizations despite incurring setup and maintenance costs at an enterprise level. Microsoft Azure Synapse Analytics adopts a pay-as-you-go model, which can lead to unpredictable expenses but offers significant ROI potential through comprehensive cloud scalability and workload optimization, making it a potentially pricier, yet robust choice for businesses.
It's not structured support, which is why we don't use purely open-source projects without additional structured support.
Not monitoring data results often in a big impact on customer services and customer perception.
They are slow to respond and not very knowledgeable.
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.
Continuous management in the way of upgrades and technical management is necessary to ensure that it remains effective.
I find the service stable as I have not encountered many issues.
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.
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.
When you scale the solution, the cloud doesn't work anymore in terms of cost.
Hadoop is a distributed file system, and it scales reasonably well provided you give it sufficient resources.
For Microsoft Azure Synapse Analytics, the integration is the most valuable feature, meaning that whatever you need is fast and easy to use.
Microsoft Azure Synapse Analytics offers significant visibility, which helps us understand our usage more clearly.
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.