

Find out what your peers are saying about Databricks, Dataiku, Amazon Web Services (AWS) and others in Data Science Platforms.
Dremio surely saves time, reduces costs, and all those things because we don't have to worry so much about the infrastructure to make the different tools communicate.
I have seen a return on investment through improved decision making, as automated distribution and uptime, along with scheduled report delivery and bursting, have eliminated various manual emailing and delays, thereby saving time and cost.
Management can now drill down and view executive summaries for new products and fraud analytics quickly, resulting in less red tape during the decision-making process.
I have seen a return on investment with significant time savings in report distribution through automation, ease of administration, and savings by keeping things secured.
We have had to reach out for customer support many times, and they respond, so they are pretty supportive about some long-term issues.
Our systems team, operating on a lot of Red Hat Enterprise Linux and maintaining long-term relations with IBM, benefits from good support coverage.
The customer support has been proactive, solution-oriented, and helpful whenever I have needed to reach out.
I rate technical support from IBM as eight out of ten, indicating a high quality of service.
Dremio's scalability can handle growing data and user demands easily.
Internally, if it's on Docker or Kubernetes, scalability will be built into the system.
I would say it is very scalable because it has continued to handle my organization's growth perfectly.
It can be scaled out to other teams, but requires building cubes and implementing policies.
IBM Cognos' scalability is very effective because it can handle a large volume of data effectively and fast.
I rate Dremio a nine in terms of stability.
I rate the stability of this solution as nine out of ten, indicating it is highly stable.
In my experience, IBM Cognos is stable, as I have not experienced any downtime or lagging issues.
Starburst comes with around 50 connectors now.
It should be easier to get Arctic or an open-source version of Arctic onto the software version so that development teams can experiment with it.
I see that many times the new versions of Dremio have not fixed old bugs, and in some new versions, old problems that were previously fixed come back again, so I think the upgrade part could use improvement.
IBM Cognos can be improved by addressing its limited real-time data connectivity, as well as enhancing the endpoint experience and mobility, which currently is not satisfactory due to limited data blending.
IBM Cognos could improve by introducing different role types, such as viewer roles, user roles, and admin roles, along with assigning minor modules to specific individuals.
IBM Cognos can be improved by addressing limited real-time data connectivity.
Our central team negotiated a different price because multiple teams within our organization use IBM Cognos, bringing the price down to around $10 to $11 per user per month.
I rate pricing as a four, meaning it is more expensive compared to other solutions.
My experience with pricing, setup cost, and licensing is positive, as the price is relatively competitive and affordable.
Having everything under one system and an easier-to-work-with interface, along with having API integrations, adds significant value to working with Dremio.
Dremio has positively impacted my organization as nowadays we are connected to multiple databases from multiple environments, multiple APIs, and applications, and Dremio organizes everything in an amazing way for me.
You just get the source, connect the data, get visualization, get connected, and do whatever you want.
The AI features in IBM Cognos helped me gain deeper insights into our business processes, enabling me to make data-driven decisions easily and understand which points need our attention and which areas of our business are performing well.
Some of the best features that IBM Cognos offers are enterprise reporting, which enables us to create, customize, and run reports on sales trends, consumer sentiment, and many more; dashboard creation; and data exploration and analysis.
Our dedicated cybersecurity team ensures that sensitive data does not become public, making it crucial that data stored in IBM Cognos remains secure throughout the entire data cycle, which is where these enterprise-grade security measures prove invaluable.
| Product | Mindshare (%) |
|---|---|
| Dremio | 2.3% |
| Databricks | 8.3% |
| Dataiku | 5.9% |
| Other | 83.5% |
| Product | Mindshare (%) |
|---|---|
| IBM Cognos | 1.3% |
| Microsoft Power BI | 8.1% |
| Tableau Enterprise | 6.0% |
| Other | 84.6% |

| Company Size | Count |
|---|---|
| Small Business | 1 |
| Midsize Enterprise | 5 |
| Large Enterprise | 5 |
| Company Size | Count |
|---|---|
| Small Business | 34 |
| Midsize Enterprise | 24 |
| Large Enterprise | 92 |
Dremio offers a comprehensive platform for data warehousing and data engineering, integrating seamlessly with data storage systems like Amazon S3 and Azure. Its main features include scalability, query federation, and data reflection.
Dremio's core strength lies in its ability to function as a robust data lake query engine and data warehousing solution. It facilitates the creation of complex queries with ease, thanks to its support for Apache Airflow and query federation across endpoints. Despite challenges with Delta connector support, complex query execution, and expensive licensing, users find it valuable for managing ad-hoc queries and financial data analytics. The platform aids in SQL table management and BI traffic visualization while reducing storage costs and resolving storage conflicts typical in traditional data warehouses.
What are Dremio's most valuable features?Dremio is primarily implemented in industries requiring extensive data engineering and analytics, including finance and technology. Companies use it for constructing data frameworks, efficiently processing financial analytics, and visualizing BI traffic. It acts as a viable alternative to AWS Glue and Apache Hive, integrating seamlessly with multiple databases, including Oracle and MySQL, offering robust solutions for data-driven strategies. Despite some challenges, its ability to reduce data storage costs and manage complex queries makes it a favorable choice among enterprise users.
IBM Cognos Business Intelligence provides a wide range of tools to help you analyze your organization's data. IBM Cognos BI allows businesses to monitor events and metrics, create and view business reports, and analyze data to help them make effective business decisions.
IBM Cognos applies techniques to describe, summarize, and compare data, and draw conclusions. This allows users to see trends and discover anomalies or variances that may not be evident by simply reading data. Data sources that contain information from different areas of a business can be stored in separate packages. Users can see only information that they have been granted access to, based on their group or role.
IBM Cognos BI consolidates the following business intelligence functions into a single web-based solution:
Reviews from Real Users
IBM Cognos stands out among its competitors for a number of reasons. Two major ones are its powerful analysis tool and its reporting capabilities.
Prasad B., a senior software engineer at a financial services firm, notes, “The product is a very good reporting tool and is very flexible. It allows for the users to get a scheduled report. We can receive automated reports as well. They are easy to schedule on a weekly or monthly basis. It is very fast. I mean in means of report output, it's very fast compared to the actual clients involved.”
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