Oracle Data Integrator (ODI) Reviews

I use the Oracle Data Integrator (ODI) for the ETL, for the ELT functions, and the integration activities to gather the data from multiple sources and integrate it into my data warehouse.

The Oracle Data Integrator (ODI) helps me optimize my data movement and transformation by allowing me to apply certain parameters, how I can use this data at the source, various options on how to place the data, and even after loading data from the files; it can help me configure the sub-link task, allowing me to move the file from one directory structure to another. It gives me the flexibility to have data aggregation done so that for analytics purposes, I don't have to query the base tables.

This whole flow of taking the data from the raw sources, loading it into fact tables, and having the right incremental load, CDC only on getting new data, and then having the option to aggregate the data for analytics purposes helps me maintain a good performance of my ETL functionalities, as well as using the core function of Oracle databases, applying partitioning on large fact tables, and having the right local partition indexing integrated with ODI helps me maintain the performance of my ELT and ETL jobs.

The best features in the Oracle Data Integrator (ODI) include its knowledge modules, easy integration, and the flexibility to apply a complex level of transformations.

ODI's declarative design approach impacts the development lifecycle as a framework; it is very easy. We can have multiple repositories and control version control and change management. We can have the development environment, quality assurance and testing environment, and production environment. We don't need to replicate our efforts in all three environments. We can do good development and migrate the complete architecture built in the development environment, do testing with the simple migration utilities that ODI facilitates.

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. It also facilitates many types of data sources, not limited to databases, flat files, XML, CSV files, and data from various database technologies including NoSQL interfaces such as Hadoop and HBase, as well as environments from the cloud. ODI helps consume diversified sources of source data and populate data in targets, not bound to any single database technology.

It would be great if ODI could link the designer, mapping, and workflows in a more simplified manner, maybe in one combined interface. 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 instead of having the designer separately, mapping separately, and monitoring and session management separately.

With respect to data quality challenges, it would be great to give an option to fix data quality issues based on AI. Integrating AI with ODI that provides recommendations on how to fix those data quality issues after analyzing and profiling business data would be excellent.

One of the main disadvantages of the Oracle Data Integrator (ODI) is that it sometimes takes a lot of resources when handling multiple jobs. The scalability and the ability to handle multiple workloads of several parallel ETL jobs could use improvement, and certain parallel threads should be added along with the ability to configure multiple jobs from the same data directory structure.

I have been working with the Oracle Data Integrator (ODI) for almost six years now.

My experience with the deployment of the Oracle Data Integrator (ODI) has been quite straightforward. It does depend on the WebLogic Server, which can sometimes be a little tricky depending on the environment we are configuring, whether it is Windows, Linux, or what kind of cluster or non-cluster we have. However, overall it is reasonable.

In terms of performance stability, I have not experienced any downtimes, crashes, or performance issues with the Oracle Data Integrator (ODI).

One of the main disadvantages of the Oracle Data Integrator (ODI) is that it sometimes takes a lot of resources when handling multiple jobs. The scalability and the ability to handle multiple workloads of several parallel ETL jobs could use improvement, and certain parallel threads should be added along with the ability to configure multiple jobs from the same data directory structure.

The technical support of Oracle is very good; they support the Oracle Data Integrator (ODI) solution effectively.

On a scale of 1 to 10, I would rate the customer service and technical support of Oracle at number nine, with 10 being the highest.

Positive

I use Informatica, SSIS, GoldenGate for various activities, as well as AWS DMS, Pentaho, Talend, Azure Data Factory, Databricks, and when I compare all these, I find some good features about ODI that are not present as easily and flexibly as they are in the ODI.

The pricing aspect of Oracle Data Integrator (ODI) is reasonable; it brings significant value to the table. It's not a product for everyone, but for those needing to handle serious business data with responsibility and objectivity, the pricing is fair.

I have experience with other products and solutions, such as Informatica and services on the AWS cloud, Azure Data Factory, and Databricks.

I work with solutions from Informatica including Azure Data Factory and Databricks, as well as AWS.

I have not integrated it with GoldenGate in my environment.

I would advise anyone considering the Oracle Data Integrator (ODI) for their organization to acknowledge that data warehouse and data integration projects are not small or short-lived; they are long-duration projects. If you are serious about managing your data in a robust manner, I definitely recommend ODI.

On a scale of 1 to 10, I rate Oracle Data Integrator (ODI) an 8 out of 10.

Positive

We are using a graphical tool called PowerDesigner to create logical and physical models. From that, we create code that can be run by Oracle Data Integrator, which then maps the data based on these models and sends it to its destination. It is currently very integrated with Oracle.

The Oracle Data Integrator facilitates complex data integration processes involving multiple countries and legal entities, which is crucial for our organization as it allows structured and efficient data management across ten countries and fifty-two legal entities.

Oracle Data Integrator offers a very good development environment and supports the use of multiple programming languages, including Python. It runs scenarios effectively, even when executing complex, long SQL scripts that are not runnable on other clients.

The Oracle Data Integrator interface is extremely slow, especially when using remote desktop connections. This impacts user experience significantly when trying to manage large repositories of metadata. Additionally, the pricing model for Oracle Cloud Services is not cost-effective for periodic usage.

It can handle complex scenarios and long SQL scripts efficiently, but the user interface performance is very slow.

Oracle support has been disappointing; they were unhelpful when we encountered an issue with a real application cluster. It took more than a week to resolve the issue due to support incompetence and delayed response time.

Positive

The pricing of Oracle Cloud Services is not favorable as it charges daily regardless of usage, unlike competitors who charge only for days used.

Google services are being considered for future integration, moving away from data tools currently used.

My advice would be to consider the impact of Oracle's slow performance on daily operations and be aware of the pricing implications of their cloud services for periodic usage.

I use Oracle Data Integrator (ODI) in the company as a data integration tool.

I have used Oracle Data Integrator (ODI)'s ELT architecture, specifically ETL. Oracle Data Integrator (ODI)'s ELT architecture has helped optimize my data movement and transformation significantly.

Adding AI capabilities would make Oracle Data Integrator (ODI) even better.

I have been working with Oracle Data Integrator (ODI) for five years.

I have no issues with Oracle Data Integrator (ODI); it functions fine.

Approximately 500 people are working with Oracle Data Integrator (ODI) in my organization now.

The deployment of Oracle Data Integrator (ODI) was mostly straightforward. I did not find any issues or difficulties with the deployment.

I was involved in the deployment of Oracle Data Integrator (ODI).

I have not measured the effectiveness of Oracle Data Integrator (ODI)'s data integration processes; I only created pipelines.

I need two administrators for Oracle Data Integrator (ODI).

I do not know if Oracle Data Integrator (ODI) is popular in my region because my organization uses only this product.

We use the product to extract data from various sources like EBS and Fusion, transform it, and load it into data warehousing systems supporting Azure, Salesforce, and KPIs.

ODI has robust ETL capabilities, particularly in its latest version. It introduced user-friendly features like drag-and-drop functionality and improved support for incremental loading, enhancing efficiency and flexibility in data integration tasks.

There could be better compatibility with other ETL tools and cloud platforms, like Azure Data Factory, ensuring seamless integration across diverse data sources and simplifying tasks such as data extraction from Excel, which currently poses challenges.

I've been utilizing Oracle Data Integrator (ODI) since 2016, primarily for ETL purposes.

While recent experiences with Oracle Cloud Analytics were positive, support for ODI-related issues in the past has sometimes been slow, impacting timely issue resolution.

The initial setup process can be complex for new users due to tasks like configuring master and work repositories. 

The platform has significantly reduced the time and effort spent on custom ETL solutions. Its automation and efficiency have translated into tangible savings in time and operational costs.

The product's knowledge module features, such as LKM (Load Knowledge Module) and IKM (Integration Knowledge Module), play a pivotal role. These modules streamline the extraction from source to staging and then to target systems, each serving specific needs like data security and integrity checks.

It effectively manages errors through its logging and exception-handling capabilities. It allows for setting constraints within mappings and notifies users of failures promptly, enabling proactive resolution of issues during data integration processes.

I would rate Oracle ODI a seven. 

We use Oracle Data Integrator as an integration tool for our data warehouse.

Oracle Data Integrator is powerful, likely the most potent tool for data integration.

There is an automated method for handling errors in the load process. However, at present, when multiple steps are executed in parallel in the load plan and errors occur, the error handling mechanism does not function correctly. This issue can be improved.

I have been using Oracle Data Integrator for seven years.

Oracle Data Integrator is a stable product.

Oracle Data Integrator is scalable.

Oracle's technical support is responsive and prompt.

I had previously used Amazon Redshift, Oracle Warehouse Builder, and Informatica before transitioning to Oracle Data Integrator.

The initial setup is neither easy nor complex; rather, it is moderate. We need to set up the complete system and its topology. First, we have to install and configure the ODI repository. Next, we need to prepare the appropriate topology, develop the necessary components, and deploy them. Typically, we separate the work of designing the repository from the execution phase. Afterward, we import it into production, where only the execution repository is present.

The implementation was completed in-house.

There are various types of ODI licenses, and the payment for each license is determined by the specific target being utilized. The license can be costly, but in certain complex cases, ODI proves to be the optimal solution.

I give Oracle Data Integrator a ten out of ten.

We have around 25 users.

For environments with simple architecture, one person is sufficient for the maintenance of Oracle Data Integrator.

Oracle Data Integrator is well-suited for large organizations; however, it may present complex integrations when dealing with heterogeneous source systems and different types of source data, especially without a skilled staff capable of adopting a rational approach to ODI. One of the standout features of ODI is its ability to prepare everything on a vertical level and create reusable components, which adds to its value.

Oracle Data Integrator (ODI) is a typical data warehouse environment, pulling the data from ERP and different systems and getting the data into the data warehouse, which is my company's use case for Oracle Data Integrator (ODI).

What I found most valuable in Oracle Data Integrator (ODI) is that it integrates well with almost all technologies currently being used in my company.

An area for improvement in Oracle Data Integrator (ODI) is real-time integration. Currently, my company has a workaround to implement real-time integration, an area on which Oracle must focus more. Real-time integration should be easier in Oracle Data Integrator (ODI).

Another area for improvement in Oracle Data Integrator (ODI) is integration with more publishers and subscribers rather than just database integrations.

Oracle Data Integrator (ODI) has features that support at least ninety percent of my organization, so it's only real-time integration that I'd like to see in the next release of the solution.

I've used Oracle Data Integrator (ODI) for around ten years, and I'm still using it.

Oracle Data Integrator (ODI) has good stability. It's much more stable compared to how it was ten years ago.

Oracle Data Integrator (ODI) is a scalable solution, for example, scaling an enterprise and implementing it for billions of projects.

My rating for the technical support provided for Oracle Data Integrator (ODI) is three out of five. That aspect still has a bit of room for improvement.

The initial setup for Oracle Data Integrator (ODI) was straightforward, and Oracle has good documentation.

The deployment for Oracle Data Integrator (ODI) was in-house.

There's ROI from Oracle Data Integrator (ODI), but I'm unsure how much my company invested and if it was a significant ROI. But definitely, there's ROI from the solution.

I have yet to determine the exact figure for Oracle Data Integrator (ODI) pricing, but it has lower pricing than Informatica.

For our current client, we didn't evaluate other solutions apart from Oracle Data Integrator (ODI), but for other clients, we evaluated Informatica and Talend. Pricing was a factor in why our clients went with Oracle Data Integrator (ODI) because Informatica has a much higher pricing than Oracle Data Integrator (ODI).

My company has around ten users of Oracle Data Integrator (ODI). A team of two to five people handles the deployment and maintenance of the solution.

The current client of my company has this plan of moving to the cloud, with the possibility of replacing the ETL tool altogether, which could mean that more data is coming up, so there may be a plan to increase the usage of Oracle Data Integrator (ODI).

My advice to others looking into implementing Oracle Data Integrator (ODI) is that if your database is on Oracle or SQL server, then Oracle Data Integrator (ODI) is a good tool to use.

My rating for Oracle Data Integrator (ODI) is seven out of ten.

ODI significantly improves data integration and management by allowing customization of data types from various sources like SQL Server databases. It automates processes with metadata, providing fast staging and building data marks. Despite some lag in development compared to newer tools, ODI remains powerful, facilitating quick integration, even across multiple companies within a corporate structure.

ODI could improve by focusing on streamlining its features without unnecessary overhead. It could also enhance seamless integration with data catalog and other tools, similar to what IBM offers with Infosphere. Additionally, strengthening integration with Oracle Analytics Services would be beneficial.

In the next release of ODI, I would like to see a focus on fixing existing features and ensuring that bug fixes from previous versions don't reappear. Improving metadata management could also be beneficial. Overall, a stronger commitment to software quality and release consistency would be a major improvement.

Oracle's technical support for ODI is generally web-based and protocol-driven, which may not always be user-friendly. However, they provide a comprehensive technical library and crash courses for maintenance personnel, earning them a seven out of ten rating in my experience. Overall, I would rate the support as a seven out of ten.

Neutral

The pricing for ODI varies depending on factors like usage and deployment model. While it might be expensive for small companies, it is generally reasonable for mid-sized companies. Pricing typically involves paying for the database and possibly additional services, with options for both on-premise and cloud deployment.

I have a strong bias for Oracle Data Integrator. It is a fantastic tool with automation, dynamic coding, and scalability features. While it was great on-premise, Oracle has been slow to modernize it. However, they are now making efforts to improve its user experience and automation in the cloud. ODI is up-to-date with cloud-based solutions and supports various technologies and databases. It has a web-based interface and can be deployed in high-availability clusters.

ODI's Knowledge Modules are vital in integration projects. They help create mappings, manage transformations, and generate SQL for Oracle metadata. By automating tasks and combining code and graphical elements, they make integration smoother and more efficient.

ODI handles data quality and consistency by allowing you to create elements within the mapping to ensure quality. You can use dummy referencing and build data quality modules as needed. While it is not a click-and-go tool, it offers flexibility to tailor data quality measures to your specific needs, making it more like traditional data warehousing.

It is hard to say if ODI is the best option on the market. It was a top choice in the past, but with evolving technologies and diverse cloud options, its position may vary. While it is strong in Oracle's cloud, other platforms like Azure might offer different advantages. Additionally, solutions like Snowflake provide more comprehensive offerings than just data integration tools like ODI.

Overall, I would rate ODI as a nine out of ten. I would recommend it to others.

We are using the solution for ETL purposes for our data warehouse.

The product has an ELT approach. It is much faster than any other ETL.

The initial setup is a bit complex compared to other tools.

I have been using the solution for three to four years.

The tool’s stability is good. I rate the stability an eight out of ten. We need to do a lot of engineering to understand the ODI mappings, knowledge modules, and how to load them. We need to learn a lot of other things, too.

It is a native tool of Oracle. It has no problems with scalability and availability. We have around 12 to 14 users.

The support depends on the severity of the tickets raised. A P1 ticket might be resolved fast. P2 or P3 tickets take a long time. I rate the support for P1 an eight out of ten, but for P2 and P3 tickets, I rate support a five out of ten.

Positive

The deployment takes at least 30 minutes. The tool has a lot of prerequisites. If we don't have a consultant or expert to help with the deployment, we won’t be able to complete it within 30 minutes. It would take longer. We must install JDK and the OBIEE repository that contains ODI packets. The software setup is confusing. The installation can be done in-house if the SOP is clear with the prerequisites and steps to follow.

The solution is very expensive. If it is cheaper, more people can use it. Oracle licensing is complex to understand. We pay a yearly licensing fee.

Since the product is expensive, we are exploring other tools like Azure Data Factory to reduce costs.

People can use the tool if they don't have a limit on their budget. However, people generally have budget constraints. We need to understand the cost before we implement the product. Overall, I rate the solution a six out of ten.

We primarily use it as a data platform for all three layers of the architecture. 

The tool improved our data integration workflow primarily due to its compatibility with Oracle. Its integration makes it very convenient for analytics. Its most valuable feature is robust extended capability. The solution's debugging capabilities are good. 

The tool should improve its pricing. It prevents the application of Oracle ODI on small and medium projects in countries like Croatia, Germany, or the US. While there are no technological obstacles to using it, the high price makes it unfeasible for projects with smaller budgets.

I've been working with Oracle ODI for about two or three months. However, I have experience with relational databases, although I haven't worked with Oracle ODI for quite some time. Recently, I returned to it for a data migration project, and I was surprised by its capabilities.

Oracle ODI is stable. 

I'm not directly dealing with end users as we specialize in IT engineering and data management. Our implementation is for a public organization with a few thousand employees. In such environments, various user profiles exist, including occasional users, heavy transactional users, etc.

The tool's support is fine. 

The setup is straightforward but designed for professional use rather than beginners. It's at a normal level of complexity for such a product.

I rate the overall solution a ten out of ten. I recommend it to anyone who has money. While the initial setup may require a modest investment, achieving optimal performance requires high proficiency in technical details. It's unsuitable for beginners and may even be challenging for those with medium-level experience.