SecondBase
Blazer
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| SecondBase | Blazer | |
|---|---|---|
| 0 | 14 | |
| 221 | 3,733 | |
| 0.0% | - | |
| 0.0 | 0.0 | |
| about 2 years ago | 4 days ago | |
| Ruby | Ruby | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
SecondBase
We haven't tracked posts mentioning SecondBase yet.
Tracking mentions began in Dec 2020.
Blazer
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Evidence – Business Intelligence as Code
And it's Open Source: https://github.com/evidence-dev/evidence
I'd also highly recommend Blazer https://github.com/ankane/blazer if you are into the Ruby on Rails world. It's super solid, and it's been an indispensable tool integrated to all my projects.
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Italian watchdog bans use of Google Analytics
I use Ahoy too, but I don't have very good visibility into the data. I should spend more time building queries and creating charts. I should probably set up blazer as well: https://github.com/ankane/blazer
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My project: railstart app
blazer
- dashboard framework
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Using Scientist to Refactor Critical Ruby on Rails Code
The Blazer gem provides a nice way to analyze the results easily. It is simple to install and allows SQL queries to run against tables. The query here shows that the candidate implementation is significantly faster than the original.
- Oldie question - latest tools?
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How to let users run scripts on their data?
There is nothing wrong with it. In Ruby on Rails, for example, you can use a gem for such a case https://github.com/ankane/blazer
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Cookie-based tracking is dead
I did server-side tracking test in a rails app, where I implemented a tracking gem called ahoy and blazer for visualization. It is very easy to set up, but a bit hard to use. Blazer can do a very basic visualization of the data if you know your SQL queries.
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Keeping the Stakes Low while Breaking Production
We then pasted that into Blazer and started looking at the SQL. As we moved around the massive SQL statement, we saw the culprit. A very narrow range for allowed article’s publication dates.
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Rails application boilerplate for fast MVP development
ahoy, ahoy_email and blazer for business intelligence
What are some alternatives?
Rails DB - Rails Database Viewer and SQL Query Runner
PgHero - A performance dashboard for Postgres
Redis Dashboard - Sinatra app to monitor Redis servers.
SchemaPlus - SchemaPlus provides a collection of enhancements and extensions to ActiveRecord
Database Cleaner - Strategies for cleaning databases in Ruby. Can be used to ensure a clean state for testing.
Scenic - Versioned database views for Rails
Upsert - Upsert on MySQL, PostgreSQL, and SQLite3. Transparently creates functions (UDF) for MySQL and PostgreSQL; on SQLite3, uses INSERT OR IGNORE.
Polo - Polo travels through your database and creates sample snapshots so you can work with real world data in development.
BatchLoader - :zap: Powerful tool for avoiding N+1 DB or HTTP queries
Foreigner - Adds foreign key helpers to migrations and correctly dumps foreign keys to schema.rb