Find out what your peers are saying about Knime, IBM, Weka and others in Data Mining.
Definitely in terms of time reduction and the speed with which data is obtained and delivered to the more business-oriented team that then has to make decisions, these two factors are important indicators.
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.
While they cannot always provide immediate answers, they are generally efficient and simplify tasks, especially in the initial phase of learning KNIME.
My mark for technical support for KNIME Business Hub is about a 7, as most of the support is in the community, and it is quite good because it is open source.
I carefully examined KNIME Business Hub resources in terms of videos, tutorials, courses, and documentation, which are very comprehensive.
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.
KNIME Business Hub scales quite well regarding data volume.
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.
For now, KNIME Business Hub is excellent for me and for our team.
From 1 to 10, I would rate the stability of KNIME Business Hub quite good, around an 8 or 9.
KNIME Business Hub is stable with small connection issues with the company data system.
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.
I would like to see additional functions in KNIME Business Hub that can connect to generative AI, allowing users to describe the workflow for easier workflow generation and creation.
When I import this data set in the File Reader node, I have problems with this field because it is a date, but the problem is that it imports it as text.
Computer vision is the most important because now there is a new age of large language models and visual language models.
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.
KNIME Business Hub has had a positive impact on my organization by leading to time savings, as many activities were automated and reduced to a morning check, whether daily or weekly, to verify that all flows had run.
KNIME is more intuitive and easier to use, which is the principal advantage.
KNIME is simple and allows for fast project development due to its reusability.
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 (%) |
|---|---|
| KNIME Business Hub | 10.6% |
| IBM SPSS Modeler | 15.5% |
| IBM SPSS Statistics | 14.9% |
| Other | 59.0% |
| Product | Mindshare (%) |
|---|---|
| Microsoft Azure Synapse Analytics | 6.2% |
| Snowflake | 15.3% |
| Databricks | 9.4% |
| Other | 69.1% |
| Company Size | Count |
|---|---|
| Small Business | 22 |
| Midsize Enterprise | 16 |
| Large Enterprise | 35 |
| Company Size | Count |
|---|---|
| Small Business | 28 |
| Midsize Enterprise | 18 |
| Large Enterprise | 60 |
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 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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