Experienced data scientists and developers are spoilt for choice when it comes to data analytics tools. But for those who don't hail from a data-centric background, it can prove to be quite a challenge.
Data operations platforms like Keboola are valuable to developers because they provide flexibility when building integrations and workflows. But Keboola is better suited for experienced data engineers and analysts who want to work in a collaborative workspace with pre-built workflows to automate data pipelines.
This is because Keboola demands advanced technical skills and experience to make sense of all the moving parts before they're leveraged to your advantage. However, you can get over the learning curve if you focus and dedicate your time and resources to becoming a Keboola expert.
If you're looking for an alternative to Keboola, we’ve got you covered. We have done the legwork and formulated a list based on factors such as ease of use, features, price, and more. This is also a list of components that can be mixed or matched to build a simpler pipeline. Here are the top 5 alternatives to Keboola:
Panoply makes syncing, storing, and accessing business data a breeze. Panoply boasts a robust data warehouse and a code-free ETL tool built for data analysts and data engineers (but it's easy enough for non-technical users).
You can set it up quickly and upkeep is minimal. Panoply allows users to query data directly within the platform or connect to their favorite BI tool or analytical notebook.
As Panoply is a data warehouse and ETL tool, no additional infrastructure is needed, eliminating any potential bottlenecks and time-intensive aspects of data management and governance. Panoply pricing is also transparent with no hidden costs.
Panoply pricing: see all pricing options; a free trial is available.
Fivetran is a cloud-based ETL tool that helps businesses of all sizes make better decisions. Fivetran supports a long list of data connectors, including Asana, Shopify, and Salesforce. You can also connect multiple applications and databases to a central data warehouse, but you'll need to have your own data warehouse, or Fivetran will provide one...for an extra cost.
Fivetran supports an extensive library of over 150 pre-built integrations. These connect to multiple databases and data generated by SaaS applications. The only downsides are it doesn't allow you to connect to services that aren't already pre-built, and Fivetran can also be expensive.
Fivetran pricing: plans are consumption-based and available upon request.
The fully managed cloud-based data warehouse, Amazon Redshift, was developed for data engineers and data scientists. Redshift comes with a built-in SQL workbench for multiple users to query data, you just need to pipe data into it to get started.
While Redshift is powerful, popular, and high performing, it lacks built-in integrations to pull in data quickly. This is a significant disadvantage as users must find third-party tools to pull in data, which requires investments of time, resources, and expertise. Like Keboola, Redshift is extremely adaptable, but it's a highly technical platform that can quickly feel overwhelming for inexperienced users.
Amazon Redshift pricing: is based on data consumption and is billed on a per-second basis (and a two-month free trial is available).
4. dbt (data build tool)
dbt is a SQL-based development environment that helps analysts take total ownership of the whole analytics engineering workflow from writing data transformation code to deployment and documentation.
As the new standard for data transformation, dbt allows you to perform complex and powerful transformations on your data. This can be done in all leading data warehouses, including BigQuery, Redshift, and Snowflake, following best practices.
What's great about dbt is that it natively supports Git integration, logging, modularity, and version control. dbt is also mostly free, open-source, and is actively supported by a large online community.
Those using this free profile have unlimited access to alerting, job scheduling, logging, and much more. However, the paid service dbt Cloud may be more attractive to larger teams, though they’ll have to pay monthly for each user and API access.
dbt pricing: collaborative analytics workflows start at $50/month (and a free trial is available).
Alteryx is a robust self-service data analytics platform that enables the preparation, blending, and analysis of data by leveraging repeatable workflows. This approach helps Alteryx facilitate faster reporting of analytics for deeper BI insights.
Alteryx also comes with multiple products with drag-and-drop functionality to ensure accessibility to ETL tools. The best part is that you don't need to be a data analytics expert or know any SQL (or programming for that matter) to build and maintain a complex data pipeline.
Popular among corporate giants like Coca-Cola and Unilever, Alteryx is also supported by a large online community. With all the learning resources available online, self-learning is possible, and the software is quite straightforward, but you'll need to connect to a data warehouse for storage.
While Alteryx is probably one of the most comprehensive, innovative, and user-friendly technologies available today, it's perhaps the most expensive data analytics tool in the marketplace. This is certainly not the right tool to start with if you're looking to build out your first data pipeline.
Alteryx pricing: starts at $5,195/user/year (or $432/month, and a free trial is available).
Comparing ETL Tools
When all your data and analytics protocols are accessible within one centralized platform, it makes a data engineer's life much easier. However, it's important to consider the profile of each user and the related costs before committing.
When you have a robust (yet user-friendly) ETL tool and data warehouse together, you can be ready to set up and deploy within minutes (without agonizing over hidden costs).
At Panoply, we strive to cover all bases by providing robust ETL pipelines and data warehousing with unparalleled support. Panoply handles disparate modern workloads efficiently, but it's also easy enough for an analyst to successfully set up and manage without expert help.