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.
AlloyDB is a fully-managed, PostgreSQL-compatible database for transactional and analytical workloads. It offers enterprise-grade performance and availability while maintaining 100% compatibility with open-source PostgreSQL. At present, AlloyDB is available globally. AlloyDB collects the various resources used in PostgreSQL deployments into a hierarchical structure that simplifies the administration and management of PostgreSQL deployments.AlloyDB works best as a back-end service. We recommend that you provide your own customer-facing service that accepts user requests and interacts with your AlloyDB cluster as required.
Microsoft SQL Server is a relational database management (RDBMS) built by Microsoft. As a database server, its primary function is to store and retrieve data upon the request of other software applications, either from the same computer or a different computer across a network—including the internet. To serve the needs of different audiences and workload sizes, Microsoft offers multiple editions (at least 12) of its Microsoft SQL Server.
AlloyDB for PostgreSQL's API provides access to a wide range of data types, including:
• Relational data: AlloyDB allows users to access and manipulate relational data stored in PostgreSQL databases.
• JSON data: AlloyDB supports JSON data types, allowing users to store and query JSON documents in PostgreSQL databases.
• Geospatial data: AlloyDB provides support for geospatial data types, allowing users to store and query spatial data in PostgreSQL databases.
• Time-series data: AlloyDB supports time-series data types, allowing users to store and query time-series data in PostgreSQL databases.
• Graph data: AlloyDB provides support for graph data types, allowing users to store and query graph data in PostgreSQL databases.
• Full-text search: AlloyDB supports full-text search capabilities, allowing users to search for text within PostgreSQL databases.
• Machine learning: AlloyDB provides support for machine learning algorithms, allowing users to perform advanced analytics on data stored in PostgreSQL databases.
Overall, AlloyDB for PostgreSQL's API provides access to a wide range of data types, making it a powerful tool for data management and analysis.
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.
