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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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- Automated schema change handling, data normalization and more
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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.
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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.
k6 Cloud is a commercial SaaS product that we designed to be the perfect companion to k6 OSS. It brings ease of use, team management, and continuous testing capabilities to your performance testing projects. k6 Cloud Docs assist you to learn and use k6 Cloud features and functionality. The k6 Cloud is a fully-managed load testing service that complements k6 to accelerate your performance testing. k6 is an open-source load testing tool and cloud service for developers, DevOps, QA, and SRE teams.
Typesense is an open-source, typo-tolerant search engine optimized for an instant (typically sub-50ms) search-like-up-type experience and developer productivity. If you've heard of Elasticsearch or Algolia, a good way to think about Typesense is that it's an open source alternative to Algolia, with some key issues fixed and an easy-to-use battery-powered alternative to Elasticsearch.It works like a CDN, but for Search. Deploy nodes around the world, closest to your users, to provide them an ultra-fast search experience.
K6 Cloud's API provides access to various types of data related to performance testing and monitoring. The following are the categories of data that can be accessed through the API:
1. Test Results: This category includes data related to the results of performance tests, such as response times, error rates, and throughput.
2. Metrics: This category includes data related to various performance metrics, such as CPU usage, memory usage, and network traffic.
3. User Behavior: This category includes data related to user behavior during performance tests, such as the number of users, their actions, and their locations.
4. Environment: This category includes data related to the environment in which the performance tests are conducted, such as the hardware and software configurations.
5. Alerts: This category includes data related to alerts generated during performance tests, such as threshold breaches and error notifications.
6. Reports: This category includes data related to performance test reports, such as summary reports, detailed reports, and trend analysis reports.
Overall, K6 Cloud's API provides a comprehensive set of data that can be used to analyze and optimize the performance of web applications and services.
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.
