Snowflake CDC: Publishing Data Using Amazon S3 and YugabyteDB
In this blog, we explore how to stream data from YugabyteDB’s Change Data Capture (CDC) feature to Snowflake through Amazon S3.
In this blog, we explore how to stream data from YugabyteDB’s Change Data Capture (CDC) feature to Snowflake through Amazon S3.
We are excited to announce that registration is now open for our fourth annual Distributed SQL Summit (DSS) 2022 on September 14th.
This virtual event will be our biggest global event to date. Additionally, a series of in-person DSS days around the world will follow this event.
The Distributed SQL Summit 2022 brings together the Distributed SQL community, customers, partners, and industry thought leaders. The goal of the event is to explore the challenges and opportunities of database modernization and transformation.
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Summer is finally here and there’s no better time to sit back and enjoy a nice, refreshing scoop! June’s monthly scoop for YugabyteDB Managed is loaded with cool new features that we are sure will get your summer started right.
In this post, we’ll explore how to run Debezium Server with Kafka as a sink using the Debezium connector for YugabyteDB.
In this blog, we’ll discover how to publish data to a Kafka topic and then read those messages to another sink, in this case a PostgreSQL database.
Kubernetes has become widely adopted in the Fortune 500. Many companies are now using the platform to run stateless and stateful applications on-premises or as hybrid cloud deployments in production. Of course, with any new technology, there are growing pains when running resilient Kubernetes workloads. But most executives and developers agree that the benefits far outweigh the challenges.
Data on the Kubernetes ecosystem is evolving rapidly with the rise of stateful applications. However,
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Log aggregation is an integral part of a distributed system. As the name suggests, a distributed system will have multiple processes across multiple machines, and each process will generate a lot of data. Looking at the data in silos is time-consuming and wouldn’t yield important information as the data sets still need to be correlated. But aggregating the logs is a huge productivity booster that helps to transform the raw log data into insightful information.
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Hello everyone! It’s Lakshmi, from the sunny (and rainy!) shores of Singapore. I am now wrapping up my Yugabyte internship, and it feels bittersweet to be penning down my thoughts on this document prior to posting it. These four months have been eventful—from the sleepless countdown to DSS Asia 2022 to interacting with a warm team that pools their strengths together.
In this post— the final installment of the series—I want to outline three lessons I have learned from my time as a Yugabyte APJ intern.
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In Part 1 and Part 2 of this blog series, we covered securing YugabyteDB through the database’s internal RPC and SQL protocols using the TLS encryption protocol. In this post, we explore how to secure communication between CQL clients and the CQL-compatible YCQL query interface of YugabyteDB, as part of the client-to-server encryption in transit setup.
Encryption in transit is a common requirement for client-to-server communication.
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When building modern web applications, developers often find data modeling and data access to be productivity bottlenecks. Rather than moving towards a schema-less database solution, many find using an ORM (object-relational mapping) tool with SQL to be their preferred option. The Node.js community has long been supportive of the Sequelize ORM, with Prisma being a newer option for those looking to model, migrate, and query their data.
In this blog, we’ll get acquainted with Prisma and how it interfaces with Node.js and YugabyteDB.
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