metriql
Redash
Our great sponsors
metriql | Redash | |
---|---|---|
7 | 38 | |
284 | 24,881 | |
0.4% | 0.9% | |
1.9 | 9.5 | |
about 1 year ago | 6 days ago | |
Kotlin | Python | |
Apache License 2.0 | BSD 2-clause "Simplified" 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.
metriql
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Getting started with a metrics store
Some of the companies that operate in space are Cube Dev; Transform(currently acquired by dbt); metriql. See more companies at https://www.moderndatastack.xyz/companies/metrics-store.
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Launch HN: Hydra (YC W22) – Query Any Database via Postgres
Presto is pretty successful but its focus is to be distributed query engine, not a proxy layer for the existing query engines. We use Trino ( formerly Presto) as our query layer and do something similar to Hydra at Metriql [1] with a fairly different use-case. Data people provide a semantic layer with the mecrics and expose them to 18+ downstream tools.
[1]: https://metriql.com
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Open source Business intelligence platform made with Python
We're using Superset to enable our analysts to explore our clients' SEM/SEO/analytics data. It also posts alerts to Slack when, say, the daily session count of a website isn't what was expected given the historical data.
Yeah, it's a little rough to get going, but once it is, we've found it to be a really powerful (and actively developed!) BI tool. It's even better with dbt + MetriQL [0], which can automatically sync Superset's dataset metadata directly with properties you set up in dbt.
Adding custom visualizations is much harder than it should be, but they're very much aware of that, and working to address it. Their Slack community is super-helpful, too.
[0]: https://metriql.com
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Show HN: Low-Code Metrics Store
As a current Looker power-user, this looks really solid.
One thing I’m not sure about though: can you use the metrics outside of the native tool, and if so how?
That is, I see Looker as a BI tool, not a metrics layer, since you mainly use the metrics you define inside Looker, not in other tools. On the other hand, something like MetriQL[0] is a pure metrics layer that can supposedly be used anywhere.
Is this both? If so, some better documentation around how to use the metrics layer would be helpful (or maybe I just didn’t look in the right place).
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Notes on the Perfidy of Dashboards
3. Define metrics in one place on top of your data models and expose the metrics to all the data tools. (This layer is new, and we're tapping it at https://metriql.com)
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Launch HN: Evidence (YC S21) – Web framework for data analysts
We use BSL license and metriql is free with a single database target. If you want to connect multiple dbt projects in a single deployment, you need to go through the sales cycle.
We work with ETL vendors that use metriql to make revenue with our BI tool integrations so we picked BSL license to be able to structure our business model in a way that you should be required to pay only if you're reselling metriql to your customers.
You can find the license here: https://github.com/metriql/metriql
Redash
- FLaNK Stack 26 February 2024
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A PostgreSQL Docker container that automatically upgrades PostgreSQL
Yeah, a lot of the time I'd agree with you.
This container came about for the Redash project (https://github.com/getredash/redash), which has been stuck on PostgreSQL 9.5 (!) for years.
Moving to a new PostgreSQL container version is easy enough for new installations, but rolling that kind of change out to an existing userbase isn't so pretty.
For people familiar with the command line, PostgreSQL, and Docker then no worries.
But a large number of Redash deployments seem to have been done by people not skilled in those things. "We deployed it from the Digital Ocean droplet / AWS image / etc!"
For those situations, something that takes care of the database upgrade process automatically is the better approach. :)
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Did anyone try Openblocks for multi-tenant client reporting?
I have tried Metabase, Redash beore (both self hosted open source versions), from my experience I find Metabase a bit easy to work with.
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Best apps for transitioning from Spreadsheets to SQLite?
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.
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Chartbrew – create live reporting dashboards from APIs, MongoDB, Firestore, etc.
Redash seems to be dead or at least in hibernation. There hasn't been a release in over a year.
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Real Time Data Infra Stack
redash
- Recommend Django Great Projects
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Framework Laptops are now Thunderbolt 4 certified
In addition to metabase there are redash[0] and apache superset[1]. They are more or less similar to metabase with some different quirks. You can also visualize quite a bit of data in grafana[2] as well.
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Is Redash dead? The red arrow indicates when Databricks acquired Redash
Source: https://github.com/getredash/redash/graphs/contributors
What are some alternatives?
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
Metabase - The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
cube.js - 📊 Cube — The Semantic Layer for Building Data Applications
bokeh - Interactive Data Visualization in the browser, from Python
Druid - Apache Druid: a high performance real-time analytics database.
PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications
matplotlib - matplotlib: plotting with Python
django-sql-explorer - Easily share data across your company via SQL queries. From Grove Collab.
superset - Apache Superset is a Data Visualization and Data Exploration Platform
folium - Python Data. Leaflet.js Maps.