Liquibase vs. Tableau Desktop

Based on my experience so far on using Liquibase in my current project, I have seen that Liquibase changelogs are version control where multiple team members and developers can work together on database and deployed automatically via CI/CD Pipeline integration using github actions and it applies same changelogs to all enviroments to remain in sync and avoid any enviroment drift. Also as Liquibase stores changelog audits in DATABASECHANGELOG table it helps in tracking purposes and to easily rollback any change . Whereas in some scenarios I feel that Liquibase have some drawbacks where if complex transformation between tables is not optimized for bulk data operations which eventually degrades database performance.

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The best scenario is definitely to collect data from several sources and create dedicated dashboards for specific recipients. However, I miss the possibility of explaining these reports in more detail. Sometimes, we order a report, and after half a year, we don't remember the meaning of some data (I know it's our fault as an organization, but the tool could force better practices).

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• Liquibase tracks changes in a metadata table contained directly in the target database, making easy administration for the DBA.
• Liquibase handles many validation tests out of the box, making it easy to choose which ones you want to include, with options for writing your own if you choose. This makes it robust and flexible in terms of validation before deployment.
• Liquibase provides easy integration into deployment pipelines for CI/CD. We use it with GitHub for source control and Circle CI for validation and deployment pipelines.

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• An excellent tool for data visualization, it presents information in an appealing visual format—an exceptional platform for storing and analyzing data in any size organization.
• Through interactive parameters, it enables real-time interaction with the user and is easy to learn and get support from the community.

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• I would like Liquibase to explore all errors in the changelog files compared to one at a time. We spent a lot of time troubleshooting one error at a time versus having a batch log of errors in each file.
• Understanding where to get support on things. I spent a lot of time researching externally to learn what the best practices were. Although I found some of the youtube videos helpful, I would like a little more of a technical support. This may be a feature with the paid tier, however, we leveraged open source.
• Seeing more examples of how others use Liquibase and their usecases will be helpful. That way we can learn from each other which may help us improve on our own deployments.

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• Pricing should be more user-friendly and usage-driven
• Making edits to the production reports is fairly tough and has a vast scope of additional capabilities
• Tableau Desktop should be able to differentiate itself from the Tableau server else there is no major meaning of two different products being offered

We are and will continue using Liquibase and it has become an integral part of our portfolio offering, any new product is by default adopting Liquibase stack.

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Our use of Tableau Desktop is still fairly low, and will continue over time. The only real concern is around cost of the licenses, and I have mentioned this to Tableau and fully expect the development of more sensible models for our industry. This will remove any impediment to expansion of our use.

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Liquibase has several features, on their free plan, that matches exactly our expectations and needs: this already makes it standout from its competitors. On top of that, the setup was straightforward: we are running an integration with Databricks, and there were only two steps truly needed, install the driver and the plugin, done. This is the type of seamless experience our team appreciates the most when evaluating a tool or service.

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Tableau Desktop has proven to be a lifesaver in many situations. Once we've completed the initial setup, it's simple to use. It has all of the features we need to quickly and efficiently synthesize our data. Tableau Desktop has advanced capabilities to improve our company's data structure and enable self-service for our employees.

When used as a stand-alone tool, Tableau Desktop has unlimited uptime, which is always nice. When used in conjunction with Tableau Server, this tool has as much uptime as your server admins are willing to give it. All in all, I've never had an issue with Tableau's availability.

Tableau Desktop's performance is solid. You can really dig into a large dataset in the form of a spreadsheet, and it exhibits similarly good performance when accessing a moderately sized Oracle database. I noticed that with Tableau Desktop 9.3, the performance using a spreadsheet started to slow around 75K rows by about 60 columns. This was easily remedied by creating an extract and pushing it to Tableau Server, where performance went to lightning fast

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Liquibase has been responsive and even is letting our group test some new products they are developing and even made code changes to their production system because of a couple bugs we have reported. Liquibase licensing has also been easy and simple. I have nothing bad to say about any of the Liquibase staff I have talked to. They also hold free information webinars for new content that helps spread adoption and moving the product forward.

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Tableau support has been extremely responsive and willing to help with all of our requests. They have assisted with creating advanced analysis and many different types of custom icons, data formatting, formulas, and actions embedded into graphs. Tableau offers a weekly presentation of features and assists with internal company projects.

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It is admittedly hard to train a group of people with disparate levels of ability coming in, but the software is so easy to use that this is not a huge problem; anyone who can follow simple instructions can catch up pretty quickly.

I think the training was good overall, but it was maybe stating the obvious things that a tech savvy young engineer would be able to pick up themselves too. However, the example work books were good and Tableau web community has helped me with many problems

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Build process takes a toll.

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Again, training is the key and the company provides a lot of example videos that will help users discover use cases that will greatly assist their creation of original visualizations. As with any new software tool, productivity will decline for a period. In the case of Tableau, the decline period is short and the later gains are well worth it.

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There is no real competitor when it comes to what Liquibase does - at least not at the time we considered it three years ago. It was an easy choice in this regard, but we could have said no to it if it made our workload more difficult. But our proof of concept showed there were easy wins to be had by implementing its software.

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I have used Power BI as well, the pricing is better, and also training costs or certifications are not that high. Since there is python integration in Power BI where I can use data cleaning and visualizing libraries and also some machine learning models. I can import my python scripts and create a visualization on processed data.

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Tableau Desktop's scaleability is really limited to the scale of your back-end data systems. If you want to pull down an extract and work quickly in-memory, in my application it scaled to a few tens of millions of rows using the in-memory engine. But it's really only limited by your back-end data store if you have or are willing to invest in an optimized SQL store or purpose-built query engine like Veritca or Netezza or something similar.

• We need to re-educate developers to use Liquibase.
• In some cases, it is hard to align when several teams work on the same DB.
• On the other hand, Liquibase provides order and consistency in managing DB changes.
• Evidence and traceability are a plus.

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• Tableau was acquired years ago, and has provided good value with the content created.
• Ongoing maintenance costs for the platform, both to maintain desktop and server licensing has made the continuing value questionable when compared to other offerings in the marketplace.
• Users have largely been satisfied with the content, but not with the overall performance. This is due to a combination of factors including the performance of the Tableau engines as well as development deficiencies.

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