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On ETL vendors to supply this functionality – though, unfortunately, just half of them score above 50% which indicates good support. More results in our survey. 5. Advanced data profiling and cleansing Most data warehouses are structurally complex, with many data sources and targets. At the same time, requirements for transformation are often fairly simple, consisting primarily of lookups and substitutions. If you have a complex transformation requirement, for example, if you need to de-duplicate your customer list, you should buy an additional module on top of the ETL solution (data profiling/data cleansing). At the very least, ETL tools provide a richer set of cleansing functions than those available in SQL. Download the ETL & Data Integration Guide to see how the ETL tools compare on these aspects. 6. Performance You might be surprised that performance is listed as one of the last under the advantages of the ETL tools. It’s possible to build a high-performance data warehouse whether you use an ETL tool or not. It’s also possible to build an absolute dog of a data warehouse whether you use an ETL tool or not. We’ve never been able to test whether an excellent hand-coded data warehouse outperforms an excellent tool-based data warehouse; we believe the answer is that it’s situational. But the structure imposed by an ETL platform makes it easier for a (novice) ETL developer to build a high-quality system. Furthermore, many ETL tools provide performance-enhancing technologies, such as Massively Parallel Processing, Symmetric Multi-Processing, and Cluster Awareness. 7. Big Data A lot of ETL tools are now capable of combining structured data with unstructured data in one mapping. In addition, they can handle very large amounts of data that don’t necessarily have to be stored in data warehouses. Nowadays, Hadoop-connectors, or similar interfaces to big data sources, are provided by almost 80% of the ETL tools. And the support for Big Data is growing continually. Open our ETL & Data Integration Guide 2025 Adoption increases for open-source ETL tools On a feature-by-feature comparison, many open-source ETL tools still can’t beat the leading closed-source offerings, but, as a

Now Frequently Asked QuestionsWhy buy an ETL tool?More than a two decades ago the vast majority of data warehouse systems were handcrafted, but the market for ETL software has steadily grown and the majority of practitioners now use ETL tools in place of hand-coded systems. Does it make sense to hand-code (SQL) a data warehouse today, or is an ETL tool a better choice?What if your favorite ETL tool is not in the list?If you think that a certain ETL tool is missing from the list above and should be included in our research, please fill out the request form and we’ll look into it straight away.How to compare the ETL vendors?In our 100% vendor independent ETL & Data Integration Guide 2025 we compare these ETL vendors as well as their solutions on 250+ key criteria that are important for selecting the right software for your organization. Do you need a solution that runs on Unix? Or Linux? Do you need a very user-friendly ETL tool? Is Data Quality important for your organization? Our guide provide all the answers to the important questions you’ll have when planning to purchase an ETL tool or data integration solution.Which vendors provide open-source ETL?Most of the vendors listed above are commercial vendors, which means that the software is not for free and that the source code isn’t available for developers. Only Pentaho, Talend, and CloverETL provide an open source ETL tool and on some aspects, they score on par with the commercial offerings.Should you use open-source ETL tools?Many organizations, both private and public, are currently evaluating or deploying Open-Source ETL tools like Talend, CloverETL, and Pentaho. These leading open-source ETL suites offer a range of ETL capabilities, ranging from ETL to ad-hoc analysis and reporting.

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It is model-driven. This paragraph summarizes the seven biggest benefits of ETL tools and offers guidance on making the right choice for your situation. 1. Visual flow The single greatest advantage of an ETL tool is that it provides a visual flow of the system’s logic (if the tool is flow-based). Each ETL tool presents these flows differently, but even the least appealing of these ETL tools compare favorably to custom systems consisting of plain SQL, stored procedures, system scripts, and perhaps a handful of other technologies. 2. Structured system design ETL tools are designed for the specific problem of data integration: populating a data warehouse or integrating data from multiple sources, or even just moving the data. With maintainability and extensibility in mind, they provide, in many cases, a metadata-driven structure to the developers. This is a particularly big advantage for teams building their first data warehouse. 3. Operational resilience Many of the home-grown data warehouses we evaluated are rather fragile: they have many emergent operational problems. ETL tools provide functionality and standards for operating and monitoring the system in production. It’s certainly possible to design and build a well-instrumented, hand-coded ETL application. Nonetheless, it’s easier for a data warehouse/business intelligence team to build on the features of an ETL tool to build a resilient ETL system. 4. Data-lineage and impact analysis We would like to be able to right-click on a number in a report and see exactly how it was calculated, where the data was stored in the data warehouse, how it was transformed, when the data was most recently refreshed, and from what source system(s) the numbers were extracted. Impact analysis is the flip side of lineage: we’d like to look at a table or column in the source system and know which ETL procedures, tables, cubes, and user reports might be affected if a structural change is needed. Figure 61: Graph showing the degree of support of impact analysis and data lineage of the major ETL tools in the market. In the absence of ETL standards that hand-coded systems could conform to, we must rely