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Kappa – Architecture Jay Kreps introduced the Kappa architecture in 2014 as an alternative to the Lambda architecture. For existing event sources, listeners are utilized to stream writes directly from database logs or similar data stores. It offers the advantage of having a single ETL platform to develop and maintain.
To keep myself sane, I use Airflow to automate tasks with simple, reusable pieces of code for frequently repeated elements of projects, for example: Web scraping ETLDatabase management Feature building and data validation And much more! What’s Airflow, and why’s it so good? What makes it my go to?
Data can come from different sources, such as databases or directly from users, with additional sources, including platforms like GitHub, Notion, or S3 buckets. Vector Databases Vector databases help store unstructured data by storing the actual data and its vector representation. mp4,webm, etc.), and audio files (.wav,mp3,acc,
As an example, an IT team could easily take the knowledge of database deployment from on-premises and deploy the same solution in the cloud on an always-running virtual machine. If you go back to 2014, data warehouse platforms were built using legacy architectures that had drawbacks when it came to cost, scale, and flexibility.
In 2014, Project Jupyter evolved from IPython. Reading & executing from.sql scripts We can use.sql files that are opened and executed from the notebook through a database connector library. connection_params: A dictionary containing PostgreSQL connection parameters, such as 'host', 'port', 'database', 'user', and 'password'.
I'm JD, a Software Engineer with experience touching many parts of the stack (frontend, backend, databases, data & ETL pipelines, you name it). With over 3 years of working with ETL pipelines and REST API integrations and development, I understand how to develop and maintain robust and scalable data systems. Let’s talk.
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