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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
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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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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.
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.
MailerLite is an intuitive email marketing solution for people of all skill levels. Simplicity is the core principle behind our solutions. We provide drag-and-drop content editors, simplified subscriber management, and advanced automation that are easy to set up. MailerLite is a distributed team of over 130 people living and working in 40 countries. Our international team enables us to better serve our customers around the world.
An object-relational database management system, PostgreSQL is able to handle a wide range of workloads, supports multiple standards, and is cross-platform, running on numerous operating systems including Microsoft Windows, Solaris, Linux, and FreeBSD. It is highly extensible, and supports more than 12 procedural languages, Spatial data support, Gin and GIST Indexes, and more. Many webs, mobile, and analytics applications use PostgreSQL as the primary data warehouse or data store.
MailerLite's API provides access to a wide range of data related to email marketing campaigns. The following are the categories of data that can be accessed through MailerLite's API:
1. Subscribers: This category includes data related to subscribers such as their email address, name, location, and subscription status.
2. Campaigns: This category includes data related to email campaigns such as the subject line, content, delivery time, and open and click-through rates.
3. Lists: This category includes data related to email lists such as the name of the list, the number of subscribers, and the date the list was created.
4. Segments: This category includes data related to segments such as the name of the segment, the criteria used to create the segment, and the number of subscribers in the segment.
5. Automation: This category includes data related to automated email campaigns such as the trigger, content, and delivery time.
6. Forms: This category includes data related to forms such as the name of the form, the number of submissions, and the date the form was created.
7. Reports: This category includes data related to email campaign reports such as the number of opens, clicks, bounces, and unsubscribes.
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.
