Search: yugabyte intern

My Experience as a YugabyteDB Engineering Intern

My Experience as a YugabyteDB Engineering Intern

I recently finished my winter 2019 term as a software engineering intern at YugaByte and it was a fantastic experience! I found the opportunity through their posting on the University of Waterloo internal job board and it was also the first time I had heard of YugabyteDB. I had previously completed two other internships at much larger companies and I was a little skeptical of startups. The fact that a friend’s internship at a startup had ended halfway due to the startup folding did not help allay my concerns.

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How PostgreSQL CDC Tools Work on YugabyteDB

How PostgreSQL CDC Tools Work on YugabyteDB

YugabyteDB speaks PostgreSQL, but do your CDC tools actually work against it? We tested three popular open-source connectors and ran them under real-world conditions. This blog shares why the compatibility holds, the one concept that matters most, and how each tool held up.

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Flink CDC for YugabyteDB

Flink CDC for YugabyteDB

Flink CDC turns YugabyteDB into a change-data-capture source for Apache Flink, so you can stream every insert, update, and delete to Kafka, a data lake, or another database in real time. This blog explains how Flink CDC works and the changes that led to the YugabyteDB integration reaching Tech Preview.

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Multi-Cloud YugabyteDB in Practice

Multi-Cloud YugabyteDB in Practice

Several recent regional and cloud-wide outages have made multi-cloud solutions more appealing. In this blog, we explore the benefits of these architectures, the considerations to keep in mind, and practical guidance for deploying a multi-cloud YugabyteDB universe.

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Deploying GraphRAG at Scale:  Unified AI Architecture with Dify and YugabyteDB

Deploying GraphRAG at Scale: Unified AI Architecture with Dify and YugabyteDB

Discover how to turn scattered documents into a connected knowledge graph using Dify and YugabyteDB. Dify handles AI orchestration while YugabyteDB serves as the unified data backbone, consolidating vectors, relationships, and metadata in one operationally straightforward platform. The end result is a robust system that’s simpler to operate, cost-efficient to scale, and easier to take from prototype to production-ready platform.

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Powering AI at Scale: Benchmarking 1 Billion Vectors in YugabyteDB

Powering AI at Scale: Benchmarking 1 Billion Vectors in YugabyteDB

Scaling to billions of vectors doesn’t require new systems or trade-offs, just YugabyteDB’s distributed PostgreSQL solution delivering simplicity, performance, and developer familiarity. We have successfully benchmarked YugabyteDB’s vector index performance with the Deep1B dataset, running a staggering one billion vectors. In this blog, we explore why scalable vector indexes are essential, share the benchmark results, and highlight the advantages of unifying vector and relational data in a single store.

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