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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
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Why choose Airbyte as the backbone of your data infrastructure?
Keep your data engineering costs in check
Get Airbyte hosted where you need it to be
- 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.
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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.
Notion is an all-in-one workspace that allows users to organize their personal and professional lives in one place. It combines features of note-taking apps, project management tools, and databases to create a customizable and flexible platform. Users can create pages, databases, and boards to manage tasks, projects, and information. Notion also offers a variety of templates and integrations with other apps to enhance productivity. Its user-friendly interface and collaborative features make it a popular choice for individuals and teams looking to streamline their workflows and stay organized.
A fully managed data warehouse service in the Amazon Web Services (AWS) cloud, Amazon Redshift is designed for storage and analysis of large-scale datasets. Redshift allows businesses to scale from a few hundred gigabytes to more than a petabyte (a million gigabytes), and utilizes ML techniques to analyze queries, offering businesses new insights from their data. Users can query and combine exabytes of data using standard SQL, and easily save their query results to their S3 data lake.
Notion's API provides access to a wide range of data types, including:
1. Pages: This includes all the pages in a Notion workspace, including their properties and content.
2. Databases: Notion's databases are a powerful way to organize and manage data. The API provides access to all the databases in a workspace, including their properties and content.
3. Blocks: Notion's blocks are the building blocks of pages and databases. The API provides access to all the blocks in a workspace, including their content and properties.
4. Users: Notion's API provides access to information about the users in a workspace, including their name, email address, and profile picture.
5. Workspaces: The API provides access to information about the workspaces themselves, including their name and ID.
6. Integrations: Notion's API allows developers to create integrations with other tools and services, such as Slack or Zapier.
Overall, Notion's API provides a comprehensive set of tools for accessing and manipulating data within a workspace, making it a powerful platform for building custom applications and workflows.
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.
