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Sync your Data
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
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Cover your custom needs with our extensibility
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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
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Reliability at every level
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Airbyte Open Source
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Airbyte Cloud
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Airbyte Enterprise
Why choose Airbyte as the backbone of your data infrastructure?
Keep your data engineering costs in check
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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.
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White-glove enterprise-level support
Including for your Airbyte Open Source instance with our premium support.
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Fnatic, based out of London, is the world's leading esports organization, with a winning legacy of 16 years and counting in over 28 different titles, generating over 13m USD in prize money. Fnatic has an engaged follower base of 14m across their social media platforms and hundreds of millions of people watch their teams compete in League of Legends, CS:GO, Dota 2, Rainbow Six Siege, and many more titles every year.
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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.
Mailgun is a well-known provider of email API services you can easily use to send, validate, and receive emails through your domain at scale. Mailgun also assists you to track the performance of your sent emails with robust open, click, bounce, and delivery tracking. It has remaining an email validation service, powered by its email-sending cache, that provides some of the most accurate validation results on the market. You can easily create personalized emails targeted at a specific audience.
DuckDB is an in-process SQL OLAP database management system. It has strong support for SQL. DuckDB is borrowing the SQLite shell implementation. Each database is a single file on disk. It’s analogous to “ SQLite for analytical (OLAP) workloads” (direct comparison on the SQLite vs DuckDB paper here), whereas SQLite is for OLTP ones. But it can handle vast amounts of data locally. It’s the smaller, lighter version of Apache Druid and other OLAP technologies.
Mailgun's API provides access to various types of data related to email delivery and management. The following are the categories of data that can be accessed through Mailgun's API:
1. Email sending and delivery data: - Information about sent emails, including sender and recipient email addresses, subject, and content. - Delivery status of emails, including whether they were successfully delivered or bounced.
2. Email tracking data: - Open and click tracking data, which provides information about when and how many times an email was opened or clicked. - Unsubscribe tracking data, which provides information about when and how many times a recipient unsubscribed from an email list.
3. Email validation data: - Information about the validity of email addresses, including whether they are formatted correctly and whether they exist.
4. Account and domain management data: - Information about the account and domain settings, including API keys, domains, and webhooks. - Usage statistics, including the number of emails sent and received, and the amount of storage used. Overall, Mailgun's API provides a comprehensive set of data that can be used to monitor and optimize email delivery and management.
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.