Find out what your peers are saying about Knime, IBM, Weka and others in Data Mining.
While they cannot always provide immediate answers, they are generally efficient and simplify tasks, especially in the initial phase of learning KNIME.
This is an underestimation of the real impact because we use big data also to monitor the network and the customer.
They are slow to respond and not very knowledgeable.
I would say the technical support for Microsoft Azure Synapse Analytics rates around six; they are friendly but there is a gap in knowledge, which makes it a little difficult to deal with.
Recovering from such scenarios becomes a bit problematic or time-consuming.
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.
I find the service stable as I have not encountered many issues.
For graphics, the interface is a little confusing.
The machine learning and profileration aspects are fascinating and align with my academic background in statistics.
Many support staff lack the necessary skills to assist with our customized requests.
Databricks is a very rich solution, with numerous open sources and capabilities in terms of extract, transform, load, database query, and so forth.
The reasons I don't rate Microsoft Azure Synapse Analytics higher include data integration and tech support being two main issues.
When you scale the solution, the cloud doesn't work anymore in terms of cost.
I find the pricing of Microsoft Azure Synapse Analytics reasonable.
It is more elastic and modern compared to SAP Data Services, allowing node creation and regrouping components or steps for reuse in different projects.
KNIME is more intuitive and easier to use, which is the principal advantage.
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.
The best feature of Microsoft Azure Synapse Analytics is the notebook functionality; it provides a very good interface, and we can easily do our experiments, POCs, and check things before migration or deployment to higher environments such as from development to SIT and then production.
| Product | Market Share (%) |
|---|---|
| KNIME Business Hub | 22.1% |
| IBM SPSS Modeler | 15.7% |
| Weka | 15.0% |
| Other | 47.2% |
| Product | Market Share (%) |
|---|---|
| Microsoft Azure Synapse Analytics | 6.2% |
| Snowflake | 17.7% |
| Dremio | 9.4% |
| Other | 66.7% |
| Company Size | Count |
|---|---|
| Small Business | 20 |
| Midsize Enterprise | 16 |
| Large Enterprise | 29 |
| Company Size | Count |
|---|---|
| Small Business | 27 |
| Midsize Enterprise | 18 |
| Large Enterprise | 54 |
KNIME Business Hub offers a no-code interface for data preparation and integration, making analytics and machine learning accessible. Its extensive node library allows seamless workflow execution across various data tasks.
KNIME Business Hub stands out for its user-friendly, no-code platform, promoting efficient data preparation and integration, even with Python and R. Its node library covers extensive data processes from ETL to machine learning. Community support aids users, enhancing productivity with minimal coding. However, its visualization, documentation, and interface require refinement. Larger data tasks face performance hurdles, demanding enhanced cloud connectivity and library expansions for deep learning efficiencies.
What are the most important features of KNIME Business Hub?KNIME Business Hub finds application in data transformation, cleansing, and multi-source integration for analytics and reporting. Companies utilize it for predictive modeling, clustering, classification, machine learning, and automating workflows. Its coding-free approach suits educational and professional settings, assisting industries in data wrangling, ETLs, and prototyping decision models.
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 Mining 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.
