ETL-Synthea
airbyte
| ETL-Synthea | airbyte | |
|---|---|---|
| 1 | 140 | |
| 94 | 14,217 | |
| - | 3.5% | |
| 6.3 | 10.0 | |
| 26 days ago | 4 days ago | |
| R | Python | |
| - | GNU General Public License v3.0 or later |
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.
ETL-Synthea
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Synthea: Open-Source Synthetic Patient Generation
I recommend the OMOP schema as a goto standard for EHR data. There's an ETL pipeline for converting Synthea output into OMOP.
https://github.com/OHDSI/ETL-Synthea
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
What are some alternatives?
Benthos - Fancy stream processing made operationally mundane
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
log-synth - Generates more or less realistic log data for testing simple aggregation queries.
dagster - An orchestration platform for the development, production, and observation of data assets.
Mage - 🧙 The modern replacement for Airflow. Mage is an open-source data pipeline tool for transforming and integrating data. https://github.com/mage-ai/mage-ai
Prefect - The easiest way to build, run, and monitor data pipelines at scale.
doris - Apache Doris is an easy-to-use, high performance and unified analytics database.
meltano
synthea - Synthetic Patient Population Simulator
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.