MuleSoft be use for ETL?
Not a big fan coding in MuleSoft Composer?
Various ETL tools have been popular since the 70s and mainly associated with data warehousing-MuleSoft.
The principle is to collect data in multiple formats from different sources, process, clean, and re-structure it before.
ETL stands for ‘extract, transform, and load.’ So, how can you use MuleSoft’s platform to achieve a better ETL integration?
Finally, store in one place.
MuleSoft has a unique approach towards modern connectivity, which differentiates its solutions from standard ETL platforms.
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Although not explicitly designed as an ETL solution, MuleSoft’s Anypoint Platform has all the tools required to perform successful data extraction and processing.
It also supports implementing a variety of connectivity patterns for ETL/ELT.
Furthermore, as a unified solution, it enables the re-use of the same building blocks to implement ETL/ELT processes faster, and consistently and, in turn, avoid error-prone processes.
- You will need a batch processing component, transformers, filters, and other MuleSoft components.
- The batch processing module enables processing a large amount of data by breaking it into chunks and storing them in a queue.
- The powerful scripting language (Data Weave) in MuleSoft – is employed for advanced data transformation and aggregation.
- Last but not least, the platform supports messaging, events, and streaming. this allows users to mix advanced integration patterns into ETL processing.
What is MuleSoft Graph QL integration? ETL
- Graph QL compared with REST, the most popular approach for designing APIs.
- And also this is a query language for APIs created by Facebook in 2012. APIs that provide a Graph QL interface are called Graph QL APIs. Is Graph QL better than REST?
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- There are loads of online articles arguing which is superior and more effective.
- Keep in mind that the main difference is that REST is an architectural style, a concept, while Graph QL is a language that specifies how to request data from a remote server.
- In spring 2021, MuleSoft added Data Graph capability to the Anypoint Platform. Applications often operate with a vast amount of data from different sources.
- Front-end developers must overcome the challenge of extracting and processing information stored in various formats while serving it without delay.
- GraphQL UI was designed to solve this problem. It offers an additional layer that exposes a single end-point, hiding the complexity of accessing diverse data sources to serve your requests.
- This approach is very much aligned with the API-led connectivity principles.
- Undoubtedly, bringing back all required information from multiple APIs in a single call and without additional code is a great advantage! GraphQL also solves REST’s over-fetching and under-fetching problems – due to its inflexibility, REST always returns a predefined set of data regardless of your exact requirements.
- Read more about how to use GraphQL to consume your REST APIs faster with DataGraph.