airbyte
superset
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airbyte | superset | |
---|---|---|
139 | 137 | |
13,923 | 58,737 | |
4.7% | 3.4% | |
10.0 | 9.9 | |
3 days ago | 3 days ago | |
Python | TypeScript | |
GNU General Public License v3.0 or later | 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.
airbyte
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Launch HN: Bracket (YC W22) – Two-Way Sync Between Salesforce and Postgres
I'l also give a shout-out to Airbyte (https://airbyte.com/), with which I've had some limited success with integrating Salesforce to a local database. The particular pull for Airbyte is that we can self-host the open source version, rather than pay Fivetran a significant sum to do this for us.
It's an immature tool, so I don't yet know that I can claim we've spent _less_ than Fivetran on the additional engineering and ops time, but it feels like it has potential to do so once stabilized.
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Who's hiring developer advocates? (October 2023)
Link to GitHub -->
- All the ways to capture changes in Postgres
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Airbyte API and Terraform Provider – available in open source
When it says "available in open source", is that under the main airbyte repo's licensing [1], hence primarily licensed under the Elastic License v2 and therefore not typically considered open source by many?
Airbyte has previous of advertising their offering as open source while not really being as per the OSD[2]. This has been raised with them previously but without response [3][4]. They've also been extending their use of ELv2, recently moving many of their existing MIT licensed connectors to be ELv2 [5].
[1] https://github.com/airbytehq/airbyte/blob/master/LICENSE
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Need help moving 16gb of mongodb data to tableau
As possible solution, I can suggest Airbyte(https://airbyte.com/). it's more performant than generic python script.
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Connecting data sources to Xata with Airbyte and Zapier integrations
Airbyte, an open-source data integration engine that offers hundreds of connectors with data warehouses and databases, has gained popularity for its seamless integration and data syncing capabilities. Xata's integration with Airbyte offers a streamlined data ingestion process from any Airbyte input source directly into your Xata database.
- Data replication from postgresql to MSSQL
- Testing
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Is it impossible to contribute to open source as a data engineer?
You can try and contribute some new connectors/operators for workflow managers like Airflow or Airbyte
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airbyte VS cloudquery - a user suggested alternative
2 projects | 2 Jun 2023
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.
What are some alternatives?
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
streamlit - Streamlit — A faster way to build and share data apps.
dagster - An orchestration platform for the development, production, and observation of data assets.
jupyter-dash - OBSOLETE - Dash v2.11+ has Jupyter support built in!
Prefect - The easiest way to build, run, and monitor data pipelines at scale.
Apache Hive - Apache Hive
meltano
lightdash - Self-serve BI to 10x your data team ⚡️
jitsu - Jitsu is an open-source Segment alternative. Fully-scriptable data ingestion engine for modern data teams. Set-up a real-time data pipeline in minutes, not days
Metabase - The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:
spark-rapids - Spark RAPIDS plugin - accelerate Apache Spark with GPUs
django-project-template - The Django project template I use, for installation with django-admin.