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Airbyte is the only open source solution empowering data teams to meet all their growing custom business demands in the new AI era.
- Inconsistent and inaccurate data
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- Deployed and governed your way
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What sets Airbyte Apart
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What our users say
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"The intake layer of Datadog’s self-serve analytics platform is largely built on Airbyte.Airbyte’s ease of use and extensibility allowed any team in the company to push their data into the platform - without assistance from the data team!"
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“Airbyte helped us accelerate our progress by years, compared to our competitors. We don’t need to worry about connectors and focus on creating value for our users instead of building infrastructure. That’s priceless. The time and energy saved allows us to disrupt and grow faster.”
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“We chose Airbyte for its ease of use, its pricing scalability and its absence of vendor lock-in. Having a lean team makes them our top criteria. The value of being able to scale and execute at a high level by maximizing resources is immense”
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.
Ashby uses a heavily-optimized infrastructure-as-a-service (IaaS) platform from Heroku and Amazon Web Services. Ashby is SOC2 compliant and Type 2 audited annually. Our SOC2 reports are available upon customer request. Ashby permits authentication from Google Workspace (formerly GSuite), Office 365 corporate accounts, Magic Links (sent via email), and SSO via SAML and OIDC. Ashby does not store any passwords. Ashby app is safe to use and requests are authentic with XSS and CSRF protection, signed and encrypted user authentication cookies, and session expiration.
Ashby's API provides access to a wide range of data related to the UK property market. The data can be categorized into the following categories:
1. Property Listings: Ashby's API provides access to a comprehensive database of property listings across the UK. This includes details such as property type, location, price, and features.
2. Property Valuations: The API also provides access to property valuation data, which can be used to estimate the value of a property based on various factors such as location, size, and condition.
3. Market Trends: Ashby's API provides access to data on market trends, including information on property prices, rental yields, and demand for different types of properties.
4. Demographics: The API also provides access to demographic data, including information on population density, age distribution, and income levels in different areas.
5. Property Ownership: Ashby's API provides access to data on property ownership, including information on the number of properties owned by individuals and companies, as well as details on property transactions.
6. Planning Applications: The API also provides access to data on planning applications, including information on the number of applications submitted, approved, and rejected in different areas.
Overall, Ashby's API provides a wealth of data that can be used by property professionals, investors, and researchers to gain insights into the UK property market.
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.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey: