From legacy data solutions to modern data cloud warehouses, data lakes & data ponds
Understand your solutions’ complexity and prepare credible migration plan before the actual journey.
Accelerate the migration efforts by automizing majority of the migration tasks.
Make sure, that the migrated solution is delivering the same results as legacy.
De-risking and accelerating your data solution migration to the cloud.
ADELE comprehends and parses as much as 80% of your legacy logic. This is a tremendous amount of work, that will accelerate your re-design and re-platforming exercise.
Kick-starting your data solution implementation in the target cloud-based platform have never been easier. With the extensive complexity assessment features of ADELE, you can plan your migration project very precisely. Use it to mitigate all the related risks in the migration excercise.
Not only ADELE accelerates your migration project, but provides reliable documentation along-side. Harvested metadata, together with data lineage and impact analysis capabilities will help you also long-term.
Increase the transparency and understanding of your data solutions. Visual interpretation of the data flows will help performing daily jobs of your data engineers and data scientists.
Obsolete data pipelines, obsolete data objects, complicated and non-performing transformation logic. This all gone with advanced optimization features of ADELE.
Coding data pipelines manually, whether in dedicated platform or directly writing them as a code is very prone to human errors. ADELE is smart, never tired and precise. Generating the jobs automatically will reduce coding errors to zero.
Providing user-friendly and intuitive features supporting you along the migration way.
Whether your legacy solution uses enterprise ETL tool or hard-coded PL/SQL procedures, ADELE provides comprehensive list of the connectors to both options. Rely fully on the ADELE's capabilities to extract knowledge and understand the logic of your data solution.
Reimplementation of the data pipelines in the target platform can be tedious job. Not only it requires a lot of efforts, but is also prone to human errors. Different coding styles can also lower the transparency of the target solution. Let ADELE generate the jobs instead and save efforts for value adding re-design of your legacy solution.
No matter whether you are building your solution from the scratch or leveraging on the existing knowledge. Write your logic in simple SQL-based queries and let ADELE generated target data pipelines.
Understanding the data flows is useful not only during the re-platforming exercise. It supports business users during daily tasks and provides the understanding of the way how certain KPIs are calculated. On the other hand, forward looking and backward looking data lineage might also answer the question of the impact of the changes on the data sources side.
Re-design and re-platforming is a process. Leverage on the comprehensive migration and metadata harvesting reports, which will guide you through your re-platforming exercise.
ADELE supports variety of the deployment models and strategies, supporting both on-premise and cloud-based data storages and data pipelines platforms.
Your legacy solution might contain obsolete codes, functionalities and data pipelines. Typical evolution of the data solution leads to work-arounds and quick fixes, which are often not documented and understood only by authors of the solution. Declutter your logic by applying variety of the optimization methods provided by ADELE.
Primarily yes, but we understand, that re-design of the solution is often made during the re-platforming exercise. That is why we support plentyful of different features covering also your re-design steps during the exercise.
Yes it can and it does. However, nowadays we see the boom of the cloud-based technologies and therefore our primary focus is on those.
Primarily no, the scope of ADELE is functionality, not data. However, data migration itself is usually easier part of the job. Make things work in the target technology, this is the challenge we are aiming at.
See page supported technologies for more details. However, for now we support extraction of the metadata / logic from PL/SQL based solution, ODI, Informatica, plain SQL and others. And the development continues.
See page supported technologies for more details. However, for now we support mainstream cloud-based solutions in AWS, MS Azure, Snowflake. And the development continues.
See dedicated page related to comparison to competitive tools and describing the benefits of the ADELE.
ADELE is none of those. ADELE does not extract, nor transform data. ADELE is producing the jobs in the target ETL / ELT platforms.
ADELE is currently hosted in Microsoft Azure. However, there are different deployment strategies. See details in page "Deployment strategies".
The product primarily does not touch data itself. We work with metadata and logic of the solution itself. Naturally, the functionality have to be proven by running the data pipelines using existing data. But it is not the precondition for the re-design and re-platforming of the solution itself.
ADELE is primarily used by data engineers, who's job is to develop the data solution in the target technology or to re-design and re-platform existing legacy solution in the target technology.
Free tier cannot be used for the commercial usage. It is also limited to one user and one environment. Support is not provided with free tier.
The price is driven by number of the objects, which are in scope of the re-design and re-platforming. The reccurent price for ADELE is then driven by the number of end users.