With the explosive growth of data in recent times and the limitations of conventional data warehouses, the Databricks Lakehouse has rapidly gained popularity as a more flexible and scalable solution for data management. By combining the best of both data lakes and data warehouses, the platform offers a more efficient and cost-effective approach to support data-driven use cases. However, the use of legacy ETL tools with the Databricks Lakehouse can pose significant challenges and ultimately block success. Let’s look at a few reasons why. 

Legacy ETL is an experts-only club 

Legacy ETL tools were originally designed for ETL developers with specific technical backgrounds and expertise in preparatory tools like Ab Initio, Informatica, or DataStage. While they can be effective in traditional data warehousing environments, which typically involve structured, pre-defined data schemas and relatively small volumes of data, they’re simply not designed to handle today’s large volumes of diverse data from multiple sources.

Data engineers working with data lakes require a high level of technical expertise to use complex platforms effectively, they’re virtually unusable by non-data engineers, such as analysts, who need to quickly transform data for their own analytics. As a consequence, data engineers find themselves burdened with repetitive tasks, leading to a delay in the timely delivery of data products. Decision makers can’t confidently provide the guidance their companies need without business intelligence. 

Proprietary problems 

Many companies find themselves stuck with outdated on-premises ETL tools that they hope to replace with cloud-based solutions. However, legacy ETL tools require customers to write business logic using their specific tool, which creates a hurdle for those trying to transition to modern cloud data platforms. As a result, if customers choose to rewrite their existing pipelines, they may end up spending millions of dollars to convert data pipelines written in proprietary legacy formats into the new formats.

Even more frustratingly, legacy ETL tools function as isolated environments (or ‘walled gardens’) that don’t integrate with the code ecosystem where significant innovation has already occurred. For instance, if a company wants to use the Amazon Deequ library for data quality alongside an existing tool, they won’t be able to. And if one team is programming while the other is using an ETL product, they can’t operate within a shared environment.

Lastly, the higher the complexity, the more expensive. Maintaining legacy tools requires a considerable investment in human resources to deal with bugs, updates, management, etc. and can result in the inefficient utilization of other infrastructure resources such as compute.

Too rigid for integration 

Finally, legacy ETL tools completely lack flexibility, making them challenging to integrate across the organization's entire spectrum. For example, they typically feature a predetermined set of visual operators, which isn’t enough for modern businesses that require many data operations. These businesses are looking to standardize routine operations to increase efficiency. However, most ETL products don’t offer first-class support for extensibility. And how we’ve come full circle, because this creates a productivity bottleneck, hindering data culture and innovation, as only expert data engineers are capable of constructing pipelines.

How Prophecy democratizes ETL for all

In order to address the data engineering bottleneck, prophecy democratizes the ETL process by removing various barriers to entry. This ultimately enables users of all skill levels to easily build, deploy, and manage data pipelines on modern cloud platforms. Here are the three ways we achieve this. 

1. Prophecy is open to all 

Prophecy runs on modern cloud architectures, like Lakehouse, which makes it easier for users to write data directly to Delta Lake, and leverage the full power of cloud-based data platforms (scalability, flexibility, and cost-effectiveness). In contrast, legacy ETL tools make it more challenging for users to shift their data pipelines to modern cloud platforms since they would need to use (and potentially learn) the tool's specific business logic. 

2. Prophecy is easy on the eyes (visual UI)

Prophecy's visual user interface is designed to be incredibly intuitive. With easy drag-and-drop functionality, it reduces the learning curve associated with building data pipelines and allows teams to be more productive and efficient with their time. All data teams, regardless of their level of technical expertise, can quickly build data pipelines, which are automatically converted to 100% open-source Spark code in either PySpark or Scala. This process guarantees translations to high-quality code, ensuring the resulting data pipelines are robust, efficient, and reliable– all without the help of engineering. 

3. Prophecy is Scalable 

Democratization doesn’t end with data teams. Prophecy’s Framework Builder helps establish standardization for common data operations, allowing for the extension of data engineering to other areas of the organization. This creates an entire culture of data, and promotes scaling of data operations across the company. With a consistent and reliable framework, data practitioners can streamline their workflows and reduce the time and effort required to implement new data operations. 

Try Prophecy for your modern ETL needs

As data volumes continue to grow and become more complex, it is becoming increasingly important for organizations to be able to more efficiently perform ETL functions. Traditional processes simply require too much time and resources, and even given the proper amount of investment, are unable to meet the demands of today's business landscape.

By modernizing the ETL process on the Lakehouse, Prophecy can provide organizations with a more agile, scalable, and cost-effective solution for managing their data. Ready to try us out? You can create a free account and get full access to all features for 14 days. Want more of a guided experience? Request a demo and we’ll walk you through how Prophecy can empower your entire data team with low-code ETL today.