
Metabase
Microsoft Power BI
Tableau
Looker
Google Data Studio
Apache Superset
D3.js
Data visualization and collaboration tool.

Metabase
AI2sql
Microsoft Power BI
Wren
Text2SQL.AI
AI Query
Cube.js
Generate optimised SQL queries in seconds

Which is more popular?
Based on our record, Redash seems to be more popular. It has been mentioned 19 times since March 2021.
Website, pricing, platforms and company facts side by side.
|
|
|
|
|---|---|---|
| Website | redash.io | querytastic.com |
| Pricing | ||
| Platforms | — | |
| Company | — | 2023 |
| Listed in |
In their own words, as submitted to SaaSHub.


No description of Redash yet.
Generate optimised SQL queries for BigQuery, DB2, Apache Flink, Apache Hive, MariaDB, MySQL, PostgreSQL, SQLite and TransactSQL in seconds
What each product offers, as listed by its team.


Possible disadvantages
An editorial look at what each product does well and who it suits.


Overall verdict
Why this product is good
Recommended for
Overall verdict
Why this product is good
Recommended for
How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing Redash and Querytastic.
Querytastic's answer:
Beautiful UI, no nonsense pricing, can invite team members
Querytastic's answer:
Developers who want to easily generate SQL queries, or people who have never used SQL before and need some help
Querytastic's answer:
I'm not good at SQL, so I built it to help me
Querytastic's answer:
Next.js, TypeScript, OpenAI
Querytastic's answer:
Its beautiful design and the fact you can easily invite team members for no extra cost
Share your experience with using Redash and Querytastic. For example, how are they different and which one is better?
External articles and on-site reviews we used to compare the two products.


Redash is a lightweight, open-source business intelligence tool designed for easy data exploration using SQL queries and interactive dashboards. It helps teams visualize, share, and collaborate on insights quickly....
Accessibility: Though it also requires support from your data team, Looker is more targeted to non-tech users than Redash, since Redash requires SQL expertise.
So all-in-all, Redash is meant for users who have the technical knowledge and depend a lot on KPIs, and Datapad is for users and businesses who just want an overview of KPI performance but quickly.
We have no reviews of Querytastic yet. Be the first one to post
Recommendations tracked on public social media and blogs since March 2021.


I am looking for service or tool similiar to Metabase or Redash that allows me to add data source - for example Postgres connection, and create raw SQL queries that can be shared or exposed through API. So instead of keeping raw SQL code... Source: about 3 years ago
I have tried Metabase, Redash beore (both self hosted open source versions), from my experience I find Metabase a bit easy to work with. Source: over 3 years ago
Regarding visualization tools, sqliteviz has proven to be the best I've found so far. Their web app runs locally but has some trackers, so I run it locally via a simple, static HTTP server. Falcon and Redash seem like overkill for my needs. Source: over 3 years ago
Tracking Querytastic since Jul 2023.
When comparing Redash and Querytastic, you can also consider the following products.

Metabase is the easy, open source way for everyone in your company to ask questions and learn from...
Compare Metabase to Redash or Querytastic:

BI visualization and reporting for desktop, web or mobile
Compare Microsoft Power BI to Redash or Querytastic:

✔️ With AI2sql, engineers and non-engineers can easily write efficient, error-free SQL queries without knowing SQL.✔️ Querying has never been easier.
Compare AI2sql to Redash or Querytastic:

Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.
Compare Tableau to Redash or Querytastic:

Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Compare Looker to Redash or Querytastic: