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[dead] 3 years ago

Please feel free to add if I've overlooked anything.

Besides all general features of sql consoles, TABLUM allows running queries on the results of the previous queries as well as mixing data from multiple data sources, and show the results in well-formatted and well-align tabular form.

Not exactly. Timing is the issue when it comes to mixed type of data sources. try to load data via the URL (e.g. the results of API invocation or rss feed), then merge it with the data from postgres sql table or data from CSV file. It becomes challenging with the listed tools. Whereas TABLUM.IO solves the issue and make it organic and fast.

You are completely right. Just wanted to add that Excel is a great product and it can be considered as a BI tool. The only thing it lacks of is data merging. You can easily merge data across sheets but it becomes a challenging task when you need to merge/“join” data from databases, especially huge datasets. This is where the self-service BI tools come into play.

TABLUM.IO simplifies data extraction/load/import from files, web and databases. You can load data from postgres, json file and application API, then merge data into a single table, display as a sheet and draw a chart for it. Wheres it is almost impossible with Excel or GoogleSheet.

I would call TABLUM.IO - a low-code tool. Power SQL user can type any complex SQL query in the SQL console. Whereas the beginners won't spend much time doing simple "SELECT" or calculating the average, they can just click on the header of the table and select "stats" to see the result.

I agree that no-code is limited to some general scenario, but there're still a lot of them.

Thus, we decided to leave an opportunity to choose which way to go: use mouse for simple / general actions or use SQL console by power users to archive some complex results.

Thanks! Well, in general they both are self-service BIs, and have common features. Yet, TABLUM.IO is focused more on faster data extraction from files e.g. you can just drag and drop JSON, XML or CSV file to load data from it. Or specify an URL for data loading from remote host. Then it is stored in a local storage as a "view" (similar to sql table). And you can work with it like it is an SQL table using sqlite syntax: JOIN with other loaded data, filter, clean up, export or generate charts. Of cause, it has connectors to popular DBs such as postgres, mysql and clickhouse.

Ultimately, we're working towards a faster data analysis so you won't spend too much time setting up connectors to files and databases. Just get the results as fast as possible.

Same with data analysis: it has embedded support for aggregate - and window-functions. You can get "MOVING AVERAGE" just clicking the table columns (no keystrokes required).

Dashboards are not yet implemented, but we're working on it.

Thanks!