SANTA CLARA, Calif.--(BUSINESS WIRE)--DataStax, the Gen AI data company, today announced a new integration with Airbyte that simplifies the process of building production-ready GenAI applications with structured and unstructured data. Now, developers can use Airbyte Cloud to easily ingest and vectorize data from hundreds of sources directly into Astra DB, the best vector database for building production-level AI applications. With the new DataStax integration, developers are able to ingest data from those sources, vectorize the data with the embedding model of their choice, and ingest and index the data and vectors into Astra DB. This dramatically simplifies and speeds up the process of building RAG (retrieval augmented generation) applications, and freeing up developers to focus on building amazing AI experiences for their end users. Developers can also use the AirByte integration with RAGStack, an out of the box solution that includes the best open-source for implementing RAG, giving enterprise developers a supported, one-stop GenAI Stack leveraging LangChain, LLamaIndex, and more

SAN FRANCISCO--(BUSINESS WIRE)--Airbyte, creators of the leading open-source data movement infrastructure, today announced availability of PyAirbyte, an open-source Python library, that makes it easy to move data across API sources and destinations by enabling Airbyte resources to be created and managed using code, rather than the user interface (UI). Python users gain access to Airbyte’s more than 250 data connectors – rather than having to build and maintain those themselves. Airbyte is the first to provide Python users this capability with availability of over 250 connectors.“A majority of existing data pipelines are written in Python today,” said Michel Tricot, co-founder and CEO, Airbyte. “We’ve seen growing demand for this capability, which provides a natural fit into the coding workflow and only requires running one command.”Python is a popular programming language for data engineers because of its simplicity, versatility, scalability, and the wide range of libraries and frameworks for data manipulation, exploration, and visualization. Python easily integrates with other tools commonly used in data analysis and data science, such as SQL databases, Hadoop, and Spark.PyAirbyte is an addition to the Airbyte API and Terraform Provider, which enable Airbyte resources to be managed programmatically – streamlining workflows and integrating Airbyte configurations with existing data infrastructure. Other deployment models include Airbyte Open Source, Airbyte Self-Managed, Airbyte Cloud, and Powered by Airbyte.Key features and benefits of PyAirbyte include the following.Programmatically manage data movement : Airbyte resources can now be created and managed through code, providing a more efficient and scalable approach for managing data pipelines.: Airbyte resources can now be created and managed through code, providing a more efficient and scalable approach for managing data pipelines

Airbyte launches first Python library for data movement, providing access to hundreds of data connectors.