#java #airbyte #connectors #data #data_analysis #data_ingestion #data_integration #data_science #data_transfers #elt #etl #incremental_updates #integration #open_source #pipeline #pipelines #replications
https://github.com/airbytehq/airbyte
https://github.com/airbytehq/airbyte
GitHub
GitHub - airbytehq/airbyte: The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to…
The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted. ...
#java #apache #data_integration #data_pipeline #etl_framework #high_performance #offline #real_time #seatunnel #sql_engine
https://github.com/apache/incubator-seatunnel
https://github.com/apache/incubator-seatunnel
GitHub
GitHub - apache/seatunnel: SeaTunnel is a next-generation super high-performance, distributed, massive data integration tool.
SeaTunnel is a next-generation super high-performance, distributed, massive data integration tool. - apache/seatunnel
#java #big_data #data_integration #data_lake #data_pipeline #data_synchronization #flink #high_performance #real_time
https://github.com/bytedance/bitsail
https://github.com/bytedance/bitsail
GitHub
GitHub - bytedance/bitsail: BitSail is a distributed high-performance data integration engine which supports batch, streaming and…
BitSail is a distributed high-performance data integration engine which supports batch, streaming and incremental scenarios. BitSail is widely used to synchronize hundreds of trillions of data ever...
#python #analytics #dagster #data_engineering #data_integration #data_orchestrator #data_pipelines #data_science #etl #metadata #mlops #orchestration #python #scheduler #workflow #workflow_automation
Dagster is a tool that helps you manage and automate your data workflows. You can define your data assets, like tables or machine learning models, using Python functions. Dagster then runs these functions at the right time and keeps your data up-to-date. It offers features like integrated lineage and observability, making it easier to track and manage your data. This tool is useful for every stage of data development, from local testing to production, and it integrates well with other popular data tools. Using Dagster, you can build reusable components, spot data quality issues early, and scale your data pipelines efficiently. This makes your work more productive and helps maintain control over complex data systems.
https://github.com/dagster-io/dagster
Dagster is a tool that helps you manage and automate your data workflows. You can define your data assets, like tables or machine learning models, using Python functions. Dagster then runs these functions at the right time and keeps your data up-to-date. It offers features like integrated lineage and observability, making it easier to track and manage your data. This tool is useful for every stage of data development, from local testing to production, and it integrates well with other popular data tools. Using Dagster, you can build reusable components, spot data quality issues early, and scale your data pipelines efficiently. This makes your work more productive and helps maintain control over complex data systems.
https://github.com/dagster-io/dagster
GitHub
GitHub - dagster-io/dagster: An orchestration platform for the development, production, and observation of data assets.
An orchestration platform for the development, production, and observation of data assets. - dagster-io/dagster
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#python #airflow #apache #apache_airflow #automation #dag #data_engineering #data_integration #data_orchestrator #data_pipelines #data_science #elt #etl #machine_learning #mlops #orchestration #python #scheduler #workflow #workflow_engine #workflow_orchestration
Apache Airflow is a tool that helps you manage and automate workflows. You can write your workflows as code, making them easier to maintain, version, test, and collaborate on. Airflow lets you schedule tasks and monitor their progress through a user-friendly interface. It supports dynamic pipeline generation, is highly extensible, and scalable, allowing you to define your own operators and executors.
Using Airflow benefits you by making your workflows more organized, efficient, and reliable. It simplifies the process of managing complex tasks and provides clear visualizations of your workflow's performance, helping you identify and troubleshoot issues quickly. This makes it easier to manage data processing and other automated tasks effectively.
https://github.com/apache/airflow
Apache Airflow is a tool that helps you manage and automate workflows. You can write your workflows as code, making them easier to maintain, version, test, and collaborate on. Airflow lets you schedule tasks and monitor their progress through a user-friendly interface. It supports dynamic pipeline generation, is highly extensible, and scalable, allowing you to define your own operators and executors.
Using Airflow benefits you by making your workflows more organized, efficient, and reliable. It simplifies the process of managing complex tasks and provides clear visualizations of your workflow's performance, helping you identify and troubleshoot issues quickly. This makes it easier to manage data processing and other automated tasks effectively.
https://github.com/apache/airflow
GitHub
GitHub - apache/airflow: Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows - apache/airflow
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#java #batch #cdc #change_data_capture #data_integration #data_pipeline #distributed #elt #etl #flink #kafka #mysql #paimon #postgresql #real_time #schema_evolution
Flink CDC is a tool that helps you move and transform data in real-time or in batches. It makes data integration simple by using YAML files to describe how data should be moved and transformed. This tool offers features like full database synchronization, table sharding, schema evolution, and data transformation. To use it, you need to set up an Apache Flink cluster, download Flink CDC, create a YAML file to define your data sources and sinks, and then run the job. This benefits you by making it easier to manage and integrate your data efficiently across different databases.
https://github.com/apache/flink-cdc
Flink CDC is a tool that helps you move and transform data in real-time or in batches. It makes data integration simple by using YAML files to describe how data should be moved and transformed. This tool offers features like full database synchronization, table sharding, schema evolution, and data transformation. To use it, you need to set up an Apache Flink cluster, download Flink CDC, create a YAML file to define your data sources and sinks, and then run the job. This benefits you by making it easier to manage and integrate your data efficiently across different databases.
https://github.com/apache/flink-cdc
GitHub
GitHub - apache/flink-cdc: Flink CDC is a streaming data integration tool
Flink CDC is a streaming data integration tool. Contribute to apache/flink-cdc development by creating an account on GitHub.
#java #apache #batch #cdc #change_data_capture #data_ingestion #data_integration #elt #high_performance #offline #real_time #streaming
Apache SeaTunnel is a powerful tool for integrating and synchronizing large amounts of data from various sources. It supports over 100 connectors, allowing you to connect to many different data sources. SeaTunnel is efficient, stable, and resource-friendly, minimizing the use of computing resources and JDBC connections. It also provides real-time monitoring and ensures data quality to prevent loss or duplication. You can use it with different execution engines like Flink, Spark, and SeaTunnel Zeta Engine. This tool is beneficial because it simplifies complex data synchronization tasks, offers high throughput with low latency, and provides detailed insights during the process. Additionally, it has a user-friendly web project for visual job management, making it easier to manage your data integration tasks.
https://github.com/apache/seatunnel
Apache SeaTunnel is a powerful tool for integrating and synchronizing large amounts of data from various sources. It supports over 100 connectors, allowing you to connect to many different data sources. SeaTunnel is efficient, stable, and resource-friendly, minimizing the use of computing resources and JDBC connections. It also provides real-time monitoring and ensures data quality to prevent loss or duplication. You can use it with different execution engines like Flink, Spark, and SeaTunnel Zeta Engine. This tool is beneficial because it simplifies complex data synchronization tasks, offers high throughput with low latency, and provides detailed insights during the process. Additionally, it has a user-friendly web project for visual job management, making it easier to manage your data integration tasks.
https://github.com/apache/seatunnel
GitHub
GitHub - apache/seatunnel: SeaTunnel is a multimodal, high-performance, distributed, massive data integration tool.
SeaTunnel is a multimodal, high-performance, distributed, massive data integration tool. - apache/seatunnel