superset
nifi
superset | nifi | |
---|---|---|
138 | 36 | |
59,473 | 4,449 | |
2.5% | 2.6% | |
9.9 | 9.9 | |
about 10 hours ago | 7 days ago | |
TypeScript | Java | |
Apache License 2.0 | Apache License 2.0 |
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.
superset
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Apache Superset
Superset is absolutely phenomenal. I really hope Microsoft eventually releases all of their customizations they made to it internally to the OS community someday.
https://www.youtube.com/watch?v=RY0SSvSUkMA
https://github.com/apache/superset/discussions/20094
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A modern data stack for startups
I recently ran a little shootout between Superset, Metabase, and Lightdash. All have nontrivial weaknesses but I ended up picking Lightdash.
Superset the best of them at _data visualization_ but I honestly found it almost useless for self-serve _BI_ by business users. This issue on how to do joins in Superset (with stalebot making a mess XD) is everything difficult about Superset for BI in a nutshell. https://github.com/apache/superset/issues/8645
Metabase is pretty great and it's definitely the right choice for a startup looking to get low cost BI set up. It still has a very table centric view, but feels built for _BI_ rather than visualization alone.
Lightdash has significant warts (YAML, pivoting being done in the frontend, no symmetric aggregates) but the Looker inspiration is obvious and it makes it easy to present _groups of tables_ to business users ready to rock. I liked Looker before Google acquired it. My business users are comfortable with star and snowflake schemas (not that they know those words) and it was easy to drop Lightdash on top of our existing data warehouse.
- FLaNK Stack Weekly for 20 Nov 2023
- Hiding tokens retrieved via API from the html source?
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Yandex open sourced it's BI tool DataLens
Or like not being able to delete a user without running some SQL:
https://github.com/apache/superset/issues/13345
Almostl instantly run into this issue setting up a test instance of Superset. And the issue has been around for years.
- Apache Superset Is a Data Visualization and Data Exploration Platform
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Apache Superset: Installing locally is easy using the makefile
Are you interested in trying out Superset, but you're intimidated by the local setup process? Worry not! Superset needs some initial setup to install locally, but I've got a streamlined way to get started - using the makefile! This file contains a set of scripts to simplify the setup process.
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More public SQL-queryable databases?
Recently I discovered BigQuery public datasets - just over 200 datasets available for directly querying via SQL. I think this is a great thing! I can connect these direct to an analytics platform (we use Apache Superset which uses Python SQLAlchemy under the hood) for example and just start dashboarding.
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How useful is SQL for managers?
if they don't want to pay for powerbi, can try something like https://superset.apache.org/
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Real-time data analytics with Apache Superset, Redpanda, and RisingWave
In today's fast-paced data-driven world, organizations must analyze data in real-time to make timely and informed decisions. Real-time data analytics enables businesses to gain valuable insights, respond to real-time events, and stay ahead of the competition. Also, the analytics engine must be capable of running analytical queries and returning results in real-time. In this article, we will explore how you can build a real-time data analytics solution using the open-source tools Redpanda a distributed streaming platform, Apache Superset, a data visualization, and a business intelligence platform, combined with RisingWave a streaming database.
nifi
- FLaNK Stack Weekly 19 Feb 2024
- Ask HN: What are some unpopular technologies you wish people knew more about?
- FLaNK Stack Weekly for 13 November 2023
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Ask HN: What low code platforms are worth using?
Apache NIFI (https://nifi.apache.org/).
It uses the concept of Flow-based programming. Also its so underacknolged but this tool is very flexible. I have used as an Event Bus all the 3rd-Party Integrations.
- Apache Nifi: easy to use, powerful, reliable system to process, distribute data
- Tool decision - What architecture would you choose and why?
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Help with choosing techstack for a new DE team
Presently setting up Apache Nifi + Apache MiNiFi for the ETL portion of my work. NiFi was easy enough to figure out; but the docs for MiNiFi have been a pain due to differences between the Java and C++ versions. I then entirely configured it with the Java version so that it was easier to search for answers for the MiNiFi yaml syntax.
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MS SQL Change Data Capture
Found it
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Is there something like airflow but written in Scala/Java?
Apache Camel Apache Nifi Spring Cloud
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Json splitting and Rerouting (new to nifi)
NIFI, like most Apache projects does most of its discussion on its mailing lists, but also has a slack.
What are some alternatives?
streamlit - Streamlit — A faster way to build and share data apps.
Logstash - Logstash - transport and process your logs, events, or other data
jupyter-dash - OBSOLETE - Dash v2.11+ has Jupyter support built in!
meltano
Apache Hive - Apache Hive
meltano - Meltano: the declarative code-first data integration engine that powers your wildest data and ML-powered product ideas. Say goodbye to writing, maintaining, and scaling your own API integrations.
lightdash - Self-serve BI to 10x your data team ⚡️
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Metabase - The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:
django-project-template - The Django project template I use, for installation with django-admin.
Apache Cassandra - Mirror of Apache Cassandra