airbyte
dbt
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airbyte | dbt | |
---|---|---|
139 | 1 | |
13,821 | 3,802 | |
4.0% | - | |
10.0 | 10.0 | |
4 days ago | over 2 years ago | |
Python | Python | |
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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Who's hiring developer advocates? (October 2023)
Link to GitHub -->
- All the ways to capture changes in Postgres
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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 20232 projects | 2 Jun 2023
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New age ETL products every data team needs to know
- https://airbyte.com/
2. Reverse ETL:
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Is it safe to update docker/docker-compose?
Here's the docker-compose file https://github.com/airbytehq/airbyte/blob/master/docker-compose.yaml
I'm trying to insall https://airbyte.com/ is a great selfhosted ELT platform. In common words, it's an app that can access all kinds of api to scrub the data and put it in a database. I really like the idea of being able to own my data and make all kinds of analyse with it.
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Top 10 Best Open Source GitHub repos for Developers 2023
AirByte GitHub: https://github.com/airbytehq/airbyte
dbt
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Open Source Analytics Stack: Bringing Control, Flexibility, and Data-Privacy to Your Analytics
Due to the rise in cloud-based data warehouses, businesses can directly load all the raw data into the data warehouse without prior transformations. This process is known as ELT (Extract, Load, Transform) and gives data and analytics teams freedom to develop ad-hoc transformations based on their particular needs. ELT became popular as the cloud's processing power and scale became better suited to transforming data. DBT (website, GitHub) is a popular open-source tool recommended for ELT and allows businesses to transform data in their warehouses more effectively. It's a great pairing with with RudderStack's Cloud Extract ETL tool.
What are some alternatives?
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
dagster - An orchestration platform for the development, production, and observation of data assets.
Apache Kafka - Mirror of Apache Kafka
Prefect - The easiest way to build, run, and monitor data pipelines at scale.
meltano
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
spark-rapids - Spark RAPIDS plugin - accelerate Apache Spark with GPUs
dbt-core - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
supabase - The open source Firebase alternative.
n8n-docs - Documentation for n8n, a fair-code licensed automation tool with a free community edition and powerful enterprise options. Build AI functionality into your workflows.
incubator-seatunnel - SeaTunnel is a distributed, high-performance data integration platform for the synchronization and transformation of massive data (offline & real-time). [Moved to: https://github.com/apache/seatunnel]
superset - Apache Superset is a Data Visualization and Data Exploration Platform