Top companies trust Airbyte to centralize their 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
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
Airbyte Open Source
Airbyte Cloud
Airbyte Enterprise
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.
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.
Ready to get started?
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.
Freshservice is a cloud-based IT service management (ITSM) software that helps businesses manage their IT services and assets. It offers a range of features including incident management, problem management, change management, asset management, and service catalog management. Freshservice allows IT teams to streamline their workflows, automate repetitive tasks, and improve communication with end-users. It also provides a self-service portal for end-users to submit and track their requests, reducing the workload on IT teams. Freshservice is designed to be user-friendly and customizable, making it suitable for businesses of all sizes and industries.
Amazon DynamoDB is a fully managed proprietary NoSQL database service that supports key–value and document data structures and is offered by Amazon.com as part of the Amazon Web Services portfolio. DynamoDB exposes a similar data model to and derives its name from Dynamo, but has a different underlying implementation.
Freshservice's API provides access to a wide range of data related to IT service management. The following are the categories of data that can be accessed through Freshservice's API:
1. Tickets: Information related to tickets such as ticket ID, status, priority, requester, assignee, and more.
2. Contacts: Details of contacts such as name, email, phone number, and more.
3. Assets: Information related to assets such as asset ID, name, type, status, and more.
4. Solutions: Details of solutions such as solution ID, title, description, and more.
5. Categories: Information related to categories such as category ID, name, and description.
6. Agents: Details of agents such as agent ID, name, email, and more.
7. Time entries: Information related to time entries such as time entry ID, description, duration, and more.
8. Business hours: Details of business hours such as business hour ID, name, start time, end time, and more.
9. SLAs: Information related to SLAs such as SLA ID, name, description, and more.
10. Surveys: Details of surveys such as survey ID, name, description, and more.
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.
