airhacks.fm podcast with adam bien cover image

airhacks.fm podcast with adam bien

High-Performance Java, Or How JVector Happened

May 18, 2024
01:01:16
An airhacks.fm conversation with Jonathan Ellis (@spyced) about:
Jonathan's first computer experiences with IBM PC 8086 and Thinkpad laptop with Red Hat Linux, becoming a key contributor to Apache Cassandra and founding datastax, starting DataStax to provide commercial support for Cassandra, early experiences with Java, C++, and python, discussion about the evolution of Java and its ecosystem, the importance of vector databases for semantic search and retrieval augmented generation, the development of JVector for high-performance vector search in Java, the potential of integrating JVector with LangChain for Java / langchain4j and quarkus for serverless deployment, the advantages of Java's productivity and performance for building concurrent data structures, the shift from locally installed software to cloud-based services, the challenges of being a manager and the benefits of taking a sabbatical to focus on creative pursuits, the importance of separating storage and compute in cloud databases, Cassandra's write-optimized architecture and improvements in read performance, DataStax's investment in Apache Pulsar for stream processing, the llama2java project for high-performance language models in Java

Jonathan Ellis on twitter: @spyced

Get the Snipd
podcast app

Unlock the knowledge in podcasts with the podcast player of the future.
App store bannerPlay store banner

AI-powered
podcast player

Listen to all your favourite podcasts with AI-powered features

Discover
highlights

Listen to the best highlights from the podcasts you love and dive into the full episode

Save any
moment

Hear something you like? Tap your headphones to save it with AI-generated key takeaways

Share
& Export

Send highlights to Twitter, WhatsApp or export them to Notion, Readwise & more

AI-powered
podcast player

Listen to all your favourite podcasts with AI-powered features

Discover
highlights

Listen to the best highlights from the podcasts you love and dive into the full episode