Wrike is a project management platform that enhances team collaboration, streamlines workflows, and boosts productivity with real-time updates, task tracking, and customizable dashboards.
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This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.
This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.
Set up a source connector to extract data from in Airbyte
Choose from one of 400 sources where you want to import data from. This can be any API tool, cloud data warehouse, database, data lake, files, among other source types. You can even build your own source connector in minutes with our no-code no-code connector builder.
Configure the connection in Airbyte
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The only open solution empowering data teams to meet growing business demands in the new AI era.
Leverage the largest catalog of connectors
Cover your custom needs with our extensibility
Free your time from maintaining connectors, with automation
- Automated schema change handling, data normalization and more
- Automated data transformation orchestration with our dbt integration
- Automated workflow with our Airflow, Dagster and Prefect integration
Reliability at every level
Ship more quickly with the only solution that fits ALL your needs.
As your tools and edge cases grow, you deserve an extensible and open ELT solution that eliminates the time you spend on building and maintaining data pipelines
Leverage the largest catalog of connectors
Cover your custom needs with our extensibility
Free your time from maintaining connectors, with automation
- Automated schema change handling, data normalization and more
- Automated data transformation orchestration with our dbt integration
- Automated workflow with our Airflow, Dagster and Prefect integration
Reliability at every level
Ship more quickly with the only solution that fits ALL your needs.
As your tools and edge cases grow, you deserve an extensible and open ELT solution that eliminates the time you spend on building and maintaining data pipelines
Leverage the largest catalog of connectors
Cover your custom needs with our extensibility
Free your time from maintaining connectors, with automation
- Automated schema change handling, data normalization and more
- Automated data transformation orchestration with our dbt integration
- Automated workflow with our Airflow, Dagster and Prefect integration
Reliability at every level
Move large volumes, fast.
Change Data Capture.
Security from source to destination.
We support the CDC methods your company needs
Log-based CDC
Timestamp-based CDC
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Keep your data engineering costs in check
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- Airbyte Cloud: Have it hosted by us, with all the security you need (SOC2, ISO, GDPR, HIPAA Conduit).
- Airbyte Enterprise: Have it hosted within your own infrastructure, so your data and secrets never leave it.
White-glove enterprise-level support
Including for your Airbyte Open Source instance with our premium support.
Airbyte supports a growing list of destinations, including cloud data warehouses, lakes, and databases.
Airbyte supports a growing list of destinations, including cloud data warehouses, lakes, and databases.
Airbyte supports a growing list of sources, including API tools, cloud data warehouses, lakes, databases, and files, or even custom sources you can build.
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FAQs
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
Wrike is an American project management application service provider which is based in San Jose, California. It is a cloud based association and project management tool that assists users to manage projects from start to finish, providing full visibility. Wrike is entirely a cloud-based project management platform for teams of 20+ which is suitable for both large program and SMBs. Wrike ransaks to discard complexity from work so people and teams can enforce at their best.
Wrike's API provides access to a wide range of data related to project management and collaboration. The following are the categories of data that can be accessed through Wrike's API:
1. Tasks: Information related to tasks such as task name, description, due date, status, and assignee.
2. Projects: Data related to projects such as project name, description, start and end dates, and project status.
3. Users: Information about users such as user name, email address, and user role.
4. Time tracking: Data related to time tracking such as time spent on tasks, time entries, and billable hours.
5. Comments: Information related to comments such as comment text, author, and date.
6. Attachments: Data related to attachments such as attachment name, type, and size.
7. Custom fields: Information related to custom fields such as field name, type, and value.
8. Folders: Data related to folders such as folder name, description, and folder structure.
9. Reports: Information related to reports such as report name, description, and report data.
Overall, Wrike's API provides access to a comprehensive set of data that can be used to enhance project management and collaboration.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
Wrike is an American project management application service provider which is based in San Jose, California. It is a cloud based association and project management tool that assists users to manage projects from start to finish, providing full visibility. Wrike is entirely a cloud-based project management platform for teams of 20+ which is suitable for both large program and SMBs. Wrike ransaks to discard complexity from work so people and teams can enforce at their best.
Wrike's API provides access to a wide range of data related to project management and collaboration. The following are the categories of data that can be accessed through Wrike's API:
1. Tasks: Information related to tasks such as task name, description, due date, status, and assignee.
2. Projects: Data related to projects such as project name, description, start and end dates, and project status.
3. Users: Information about users such as user name, email address, and user role.
4. Time tracking: Data related to time tracking such as time spent on tasks, time entries, and billable hours.
5. Comments: Information related to comments such as comment text, author, and date.
6. Attachments: Data related to attachments such as attachment name, type, and size.
7. Custom fields: Information related to custom fields such as field name, type, and value.
8. Folders: Data related to folders such as folder name, description, and folder structure.
9. Reports: Information related to reports such as report name, description, and report data.
Overall, Wrike's API provides access to a comprehensive set of data that can be used to enhance project management and collaboration.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
Wrike is an American project management application service provider which is based in San Jose, California. It is a cloud based association and project management tool that assists users to manage projects from start to finish, providing full visibility. Wrike is entirely a cloud-based project management platform for teams of 20+ which is suitable for both large program and SMBs. Wrike ransaks to discard complexity from work so people and teams can enforce at their best.
Wrike's API provides access to a wide range of data related to project management and collaboration. The following are the categories of data that can be accessed through Wrike's API:
1. Tasks: Information related to tasks such as task name, description, due date, status, and assignee.
2. Projects: Data related to projects such as project name, description, start and end dates, and project status.
3. Users: Information about users such as user name, email address, and user role.
4. Time tracking: Data related to time tracking such as time spent on tasks, time entries, and billable hours.
5. Comments: Information related to comments such as comment text, author, and date.
6. Attachments: Data related to attachments such as attachment name, type, and size.
7. Custom fields: Information related to custom fields such as field name, type, and value.
8. Folders: Data related to folders such as folder name, description, and folder structure.
9. Reports: Information related to reports such as report name, description, and report data.
Overall, Wrike's API provides access to a comprehensive set of data that can be used to enhance project management and collaboration.
1. Open the Airbyte dashboard and click on "Sources" from the left-hand menu.
2. Click on "Create New Source" and select "Wrike" from the list of available connectors.
3. Enter a name for your Wrike source connector and click on "Next".
4. Enter your Wrike API credentials, including your Client ID, Client Secret, and Access Token. You can find these credentials by following the instructions in the Wrike API documentation.
5. Click on "Test Connection" to ensure that your credentials are correct and that Airbyte can connect to your Wrike account.
6. Once the connection is successful, select the Wrike entities that you want to replicate in Airbyte. You can choose from tasks, folders, projects, and more.
7. Configure any additional settings for your Wrike source connector, such as the replication frequency and the number of records to fetch per API call.
8. Click on "Create Source" to save your Wrike source connector and start replicating data from Wrike to Airbyte.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.
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