


Find out what your peers are saying about Informatica, Microsoft, Qlik and others in Data Integration.
It provides a positive return on investment for those who can connect multiple data sources and make data-driven decisions easily.
If you don't need to write a whole ETL to make the data virtualization, you need way fewer people to write a query instead of writing an ETL pipeline.
I have seen a return on investment, which showed up in improved customer satisfaction scores.
They have a good methodology for learning how to use the tool.
Denodo's customer support team is very competent and responsive.
If we raise a ticket, it can be resolved or addressed within a reasonable time frame, so support is good.
We also have the flexibility to submit a feature request to be included as part of the wishlist, potentially becoming a product feature in subsequent releases.
I rate their support as nine on a scale from one to ten.
IBM tech support has allocated dedicated resources, making it satisfactory.
I can get solutions quickly, and any tickets I submit to Oracle are responded to and resolved rapidly.
The technical support of Oracle is very good; they support the Oracle Data Integrator (ODI) solution effectively.
For huge data requests, it cannot scale automatically; admin action is required.
Denodo's scalability comes into play specifically when there is data transfer.
My client has almost 100 million records, and the performance was impacted in a way that required optimization.
If the job provided suggestions about running this kind of parallel processing and how many virtual nodes are required, it would help.
The scalability and the ability to handle multiple workloads of several parallel ETL jobs could use improvement.
I would rate it nine out of ten because it is very reliable, always performing as expected.
If JVM does not function properly, it may cause Denodo to fail to connect to different sources.
Denodo is stable and good.
In terms of performance stability, I have not experienced any downtimes, crashes, or performance issues with the Oracle Data Integrator (ODI).
Ensuring data caching is up to date is critical.
Denodo needs better communication on how the product can be deployed for specific solutions.
The system has dependencies on other environments, like JVM, which can affect its performance.
If the job itself gave some guidance, such as running this parallel processing with this many nodes, it would help; I think that is missing.
I wonder if it supports other areas, such as cloud environments with open source support, or EdgeShift.
The solution needs improvement in connectivity with big data technologies such as Spark.
If I use a source system like Oracle and a target system like Teradata, ODI will still run, but it struggles a bit with different infrastructures.
It would be excellent not to have to go into different areas to perform different activities but rather have a user-defined interface where we can configure a job, run it, monitor it, link packages, and link subprocesses all in one frame.
Adding AI capabilities would make Oracle Data Integrator (ODI) even better.
For small companies, it's not a solution that most small companies can afford.
Denodo is considered pricey, limiting its use to large enterprises or government organizations that can afford its comprehensive setup.
Denodo's pricing is not affordable for small companies and is more suitable for medium to large enterprises.
Pricing for IBM InfoSphere DataStage is moderate and not much expensive.
ODI is cheaper compared to Informatica PowerCenter and IBM DataStage.
The pricing aspect of Oracle Data Integrator (ODI) is reasonable; it brings significant value to the table.
Denodo's ability to connect to multiple data sources and perform extract-transform-load (ETL) operations on the fly is noteworthy.
The most valuable feature of Denodo is its uniformity of self-site data access types, which allows it to connect to almost any storage technology and feed it transparently.
Denodo supports SQL base, so if you want to join two tables or two views, you can use SQL, which is an advantage as most developers or business people know SQL.
It is straightforward from a design and development perspective, and also for deployment.
As we are a financial organization, security is our main concern, so we prefer enterprise tools.
I have leveraged IBM InfoSphere DataStage's integration with IBM's Information Server suite, and it is indeed beneficial.
The main benefits that Oracle Data Integrator (ODI) brings to the table include data quality, data completeness functionality, metadata management, and the reverse engineering feature, which allows integrating the metadata of diversified data sources with a single click.
Oracle Data Integrator (ODI) is powerful and strong if my system uses Oracle components for environments like OLTP, enterprise data warehouse, or data marts.
Oracle Data Integrator (ODI)'s ELT architecture has helped optimize my data movement and transformation significantly.
| Product | Mindshare (%) |
|---|---|
| Denodo | 1.3% |
| Oracle Data Integrator (ODI) | 2.2% |
| IBM InfoSphere DataStage | 1.6% |
| Other | 94.9% |


| Company Size | Count |
|---|---|
| Small Business | 16 |
| Midsize Enterprise | 6 |
| Large Enterprise | 21 |
| Company Size | Count |
|---|---|
| Small Business | 23 |
| Midsize Enterprise | 4 |
| Large Enterprise | 26 |
| Company Size | Count |
|---|---|
| Small Business | 26 |
| Midsize Enterprise | 12 |
| Large Enterprise | 44 |
Denodo specializes in data virtualization, data cataloging, and user-friendly interfaces. It's recognized for connecting disparate data sources, presenting unified data for analytics, and supporting efficient decision-making with agile analytics and robust data governance.
Denodo effectively aggregates data from multiple sources to offer a comprehensive understanding through its virtualization capabilities. It provides role-based access control, flexible query languages, performance optimization, and integration with databases. Enhancements are needed in its interface and documentation to ensure better user experiences. While the platform supports cloud migration, integration challenges with tools like Salesforce and MuleSoft exist. Improvements in data visualization, automation, and scalability, especially in large data environments, are critical areas for growth.
What are the key features of Denodo?In industries like finance, healthcare, and retail, Denodo plays a crucial role in data virtualization and integration. Organizations use it to unify disparate data systems, enabling real-time analytics and supporting cloud migrations. Denodo's platform is ideal for businesses needing to aggregate, transform, and utilize diverse data efficiently, optimizing operations and enhancing governance.
IBM InfoSphere DataStage offers powerful ETL capabilities focusing on data transformation and integration, ensuring seamless data processing and management in complex environments. It is particularly valued for handling extensive data volumes with robust transformation features and scalability options.
IBM InfoSphere DataStage is renowned for its strength in data extraction, transformation, and loading, making it a preferred choice for businesses handling large datasets. It provides extensive database connectors, integrates efficiently with existing systems, and facilitates complex data transformations. Users appreciate its scalability, metadata management, and effectiveness in applying business rules. Despite this, areas for improvement include enhanced cloud integration, better error messaging, and expanded connectivity with modern databases. Its pricing scheme and deployment complexity also present considerations for potential users.
What are the key features of IBM InfoSphere DataStage?Businesses in sectors like telecommunications, banking, and insurance commonly implement IBM InfoSphere DataStage for ETL processes. It's used for integrating data from multiple sources into data warehouses, supporting business intelligence initiatives, and managing data quality. Known for efficiently handling integration of mainframes and Oracle databases, it supports complex data projects tailored to industry needs.
Oracle Data Integrator offers flexible EL-T architecture, optimizing processing with database capabilities. It supports diverse data sources, automates deployment, and provides efficient data transformations, making it suitable for data warehousing and complex data environments.
Oracle Data Integrator leverages EL-T architecture to enhance processing by utilizing database strengths. It integrates with a wide array of technologies, including RDBMS, cloud, and big data. The software's Knowledge Modules enable customizable integration strategies, accelerating development. With a user-friendly interface and automation features, it simplifies metadata management and supports real-time data warehousing. Key areas such as UI performance, integration, and real-time data capabilities require enhancements. Challenges include error handling, initial setup, and compatibility with platforms like Git, Azure, and IoT services. Improvements in metadata management, scalability, and user-friendliness are needed.
What are the most important features of Oracle Data Integrator?Organizations utilize Oracle Data Integrator primarily in data warehousing, handling data from ERP systems, EBS, Fusion, and cloud databases. It aids in creating data lakes, OLTP migrations, digital health initiatives, and automation tasks, ensuring seamless integration with databases like MySQL and SQL Server.