DbVisualizer vs. Hevo Data

Seamlessly querying PostgreSQL/PostGIS, Oracle, SQL Server, and SQLite from one interface without switching tools. The intelligent autocomplete and schema browsing make it ideal for writing queries and understanding unfamiliar databases. Complex performance tuning, deep monitoring, and automated backup/recovery require specialized DBA tools. Performance degrades with tens or hundreds of thousands of rows; command-line tools or ETL solutions are better suited to bulk data processing.

Incentivized

It is of great help for unstructured data sources. The way Hevo Data flattens the high nested data is amazing. Schema management is also good by Hevo Data. The way it's tell about the data type and then we can identify any error in the model. Additionally, It is very easy to setup for any new user and once model is created then we do not have to worry about the script maintenance and updating the script daily.

Incentivized

• Out-of-the-box support for many different databases.
• Intuitive UI for interacting with data.
• Flexibility of SQL Commander for writing scripts.
• Great support for working with JSON data in recent updates.
• Database connections over SSH.
• Table relationship visualization is very helpful.
• The tree view is well organized in how it splits out schemas.

• Extract
• Load
• Transform
• Support

Incentivized

• Small, but noticeable: it would be nice to be able to highlight just one column of a data output for copy/paste by clicking on the column header (a feature some of us are accustomed to from SQL Server Management Studio)
• Is there an ability to bulk import an excel file to a table in a connected SQL Server in DbVis? If so, I haven't figured that out yet. I still largely use Microsoft SSMS to import data to our team's personal SQL Server, but can easily query that server via DbVis)
• (I really don't have any major complaints - our company has tried to steer users toward DBeaver for YEARS, which I cannot stand. DbVis knocks the beaver out of the water)

• Support - their support teams try to be helpful, but often miss the mark
• Error logging - we've run into a few issues debugging errors and limited support is provided by Hevo

Incentivized

We never had problems with it. It is able to connect to all data sources (Oracle, Informix, DB2, SQL Server) that we currently use.

Incentivized

It does what we need it for, which is manipulate data, check connections, visualize database structures, check on user rights, or even just version checks on the used databases. The 'type to get to table name' feature is often irrational in behaviour, which leads to frustration. The start-up time could be much better, and the UI changes between versions are sometimes a hassle for us when buttons are suddenly moved or their appearance changes. We use a wide variety of DBVis versions on customer installations (which use the once-bought version), and differences in the look and feel between versions sometimes slow us down.

Never used

Incentivized

[DbVisualizer] is pretty easy to use compared to IntelliJ because of it's simplicity. The performance is very good, it feels as good as a native application compared to the other two softwares I used for the same purpose. It's very cheaper compared to the other two tools and that's a big selling point.

Incentivized

1. Cost efficient 2. Creation of automated pipeline 3. Can load data from multiple data sources 4. Updates data in near real-time - We were able to get near real time insights from the data model which we have created in hevo 5. It has good integration with different BI tools

Incentivized

• Positive: Real time saver when working across multiple databases. At least 30-40 mins a day are saved
• Positive: Helpful for the 'quick DBA' tasks without switching to the native tools: approx 1-2 hours saved weekly
• Positive: Easy switch between environments / schemas / etc without hassle: saved at least an hour daily

• Comprehensive results from the data processing is a perfect approach from the tool.
• Authentic data models brings a high automation process and more productivity.
• Expansive data sourcing brings clarity and genuine results after inferential analytics.

Incentivized