Informatica IDMC and Apache Airflow are leading players in the data management and workflow orchestration market. Informatica IDMC holds an upper hand in MDM capabilities and comprehensive feature offerings, while Apache Airflow excels in flexibility due to its open-source nature.
Features: Informatica IDMC stands out with its robust data integration, quality management, and flexible task-based workflow engine. Key features include data cleansing and validation, integration with PowerCenter, and support for flexible architectures. Apache Airflow is recognized for its flexibility in defining workflows programmatically using Python. It provides powerful orchestration of data pipelines and is highly adaptable due to its open-source nature.
Room for Improvement: Informatica IDMC could enhance integration, particularly with SAP, introduce preconfigured business rules, and improve user stewardship and reporting interfaces. Apache Airflow faces challenges with handling cyclic workflows and state management, requiring external state repositories, and needs better documentation and support for more programming languages.
Ease of Deployment and Customer Service: Informatica IDMC provides versatile deployment options across on-premises, hybrid, and public cloud environments, with responsive customer service although sometimes delayed. Apache Airflow, while easily deployable, heavily relies on user expertise and community-driven support, lacking formal customer service like Informatica.
Pricing and ROI: Informatica IDMC is noted for higher pricing due to its extensive features and scalability, targeted at large enterprises, potentially limiting small business adoption. Apache Airflow benefits from a cost advantage as an open-source solution, eliminating licensing fees and appealing to budget-conscious organizations, though ROI depends on effective open-source utilization.
We see return on investment from this solution in terms of time; time reduction or cost benefits is what we are getting very good results from.
There is enough documentation available, and the community support is good.
Forums and community resources like Stack Overflow are helpful.
Due to the tool's maturity limitations, solutions are not always simple and often require workarounds.
The response time is pretty good because we have someone in-house, who is an expert from Informatica, in our team who can help us with any sort of queries usually.
If they are unsure how to resolve an issue, they keep customers informed, providing updates about progress and ensuring communication with the product team to deliver accurate responses.
The solution is very scalable.
Apache Airflow scales well, especially when deployed in Kubernetes environments.
As a SaaS platform, IDMC is quite scalable and provides complete flexibility.
I find Informatica Intelligent Data Management Cloud (IDMC) to be a sustainable and scalable solution.
I would rate the stability of the solution as ten out of ten.
Apache Airflow is stable and I have not experienced significant issues.
I would rate its stability at nine out of ten.
Stability is crucial because IDMC holds business-critical data, and it needs to be available all the time for business users.
It is not suitable for real-time ETL tasks.
There is no dashboard for us to check all the Directed Acyclic Graphs (DAGs); a dashboard would help us analyze the work better.
If we desire to add custom messengers or a rest API, those options are unavailable.
The tool needs to mature in terms of category-specific attributes or dynamic attributes.
I also want to see integration with other Informatica products, such as IICS, to leverage the metadata from EDC.
The licenses are too expensive compared to before, which is why customers are now preferring other data metadata management tools like OneTrust, Collibra, and Azure Purview.
I prefer using the open-source version rather than the enterprise version, which helps manage costs.
It is a sub-feature and not an individual purchase.
Apache Airflow is a community-based platform and is not a licensed product.
It ranges from a quarter million to a couple of million a year.
The licenses are too expensive compared to before, which is why customers are now preferring other data metadata management tools like OneTrust, Collibra, and Azure Purview.
I think the costs are reasonable for the kinds of features that Informatica Intelligent Data Management Cloud (IDMC) has.
Apache Airflow is an open-source platform that allows easy integration with AWS, Azure, and Google Cloud Platform.
Reliability is good, and when integrated with Kubernetes, it performs better compared to on-premises environments.
We can create notifications for successful or failed tasks, providing a practical way to monitor our workflows.
The platform's ability to pull in data from other platforms without the need for an additional integration tool enhances its appeal.
Informatica Intelligent Data Management Cloud (IDMC) can connect to pretty much any application, including Oracle Analytics and Power BI, and it works quite seamlessly.
In on-premise, we call it EDC for metadata management, while in cloud-based technologies, it is known as the Metadata Command Center, which serves the same purpose as EDC concerning CDGC.
| Product | Market Share (%) |
|---|---|
| Apache Airflow | 5.7% |
| Informatica Intelligent Data Management Cloud (IDMC) | 1.4% |
| Other | 92.9% |
| Company Size | Count |
|---|---|
| Small Business | 13 |
| Midsize Enterprise | 3 |
| Large Enterprise | 24 |
| Company Size | Count |
|---|---|
| Small Business | 42 |
| Midsize Enterprise | 24 |
| Large Enterprise | 134 |
Apache Airflow is an open-source workflow management system (WMS) that is primarily used to programmatically author, orchestrate, schedule, and monitor data pipelines as well as workflows. The solution makes it possible for you to manage your data pipelines by authoring workflows as directed acyclic graphs (DAGs) of tasks. By using Apache Airflow, you can orchestrate data pipelines over object stores and data warehouses, run workflows that are not data-related, and can also create and manage scripted data pipelines as code (Python).
Apache Airflow Features
Apache Airflow has many valuable key features. Some of the most useful ones include:
Apache Airflow Benefits
There are many benefits to implementing Apache Airflow. Some of the biggest advantages the solution offers include:
Reviews from Real Users
Below are some reviews and helpful feedback written by PeerSpot users currently using the Apache Airflow solution.
A Senior Solutions Architect/Software Architect says, “The product integrates well with other pipelines and solutions. The ease of building different processes is very valuable to us. The difference between Kafka and Airflow, is that it's better for dealing with the specific flows that we want to do some transformation. It's very easy to create flows.”
An Assistant Manager at a comms service provider mentions, “The best part of Airflow is its direct support for Python, especially because Python is so important for data science, engineering, and design. This makes the programmatic aspect of our work easy for us, and it means we can automate a lot.”
A Senior Software Engineer at a pharma/biotech company comments that he likes Apache Airflow because it is “Feature rich, open-source, and good for building data pipelines.”
Informatica Intelligent Data Management Cloud (IDMC) integrates data quality, governance, and integration with flexible architecture. It supports multiple domains and a data models repository, delivering AI-enhanced data management across cloud-native platforms.
IDMC provides seamless integration and governance capabilities that support diverse data environments. Its comprehensive suite includes customizable workflows, data profiling, and metadata management. AI features, a data marketplace, and performance scalability enhance data management. While its interface poses challenges, its robust matching and cloud-native integration facilities are essential for complex data ecosystems. Users employ IDMC for connecting systems, ensuring data quality, and supporting data compliance but seek better pre-built rules, services, and improved connectivity, especially with platforms like Salesforce. Licensing, cost, and added AI functionalities are areas for potential refinement.
What are the key features of IDMC?IDMC is implemented across industries for data integration, metadata management, and governance. Organizations use it to connect systems, migrate data to cloud environments, and maintain data quality. They manage master data and automate business processes, facilitating data lineage and ensuring compliance with privacy regulations.
We monitor all Business Process Management (BPM) 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.
