Finding one-to-one mapping of the differences between monolithic and cloud-native databases is difficult.
In this blog, we compare YugabyteDB and Oracle (RAC, Data Guard) via availability objectives.
This should help you understand how Oracle MAA options map to YugabyteDB’s intrinsic features when considering migration projects.
In Java development, garbage collection is a routine task. Applications generate garbage all the time. And that garbage is meticulously cleaned out by CMS, G1, Azul C4 and other types of collectors. Basically, our applications are born to bring value to this world, but nothing is perfect—including our applications that leave litter in the Java heap.
However, the story doesn’t end with the Java heap. In fact, it only starts there. Let’s take the example of a basic Java application that uses a relational database—such as PostgreSQL—and solid state drives (SSDs) as a storage device.
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It’s been a while since YugabyteDB came out with Change Data Capture (CDC) using Debezium, an open source distributed platform. You can just fire it up as a plugin for Kafka connect and then it will start publishing all the changes in your database to a Kafka topic.
The Debezium Connector for YugabyteDB CDC is our addition to the list of Debezium connectors. It also provides support for reading changes from a YugabyteDB database.
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In this blog post, we will stream data to downstream databases leveraging YugabyteDB’s Change Data Capture (CDC) feature introduced in YugabyteDB 2.13. This will publish the changes to Kafka and then stream those changes to databases like MySQL, PostgreSQL, and Elasticsearch.
The diagram below represents how data will flow from YugabyteDB to Kafka and then further to the sink databases.
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Recently, I came across a sample e-commerce application that demonstrates how to use Next.js, GraphQL engine, PostgreSQL, and a few other frameworks to build a modern web application. The application supports basic e-commerce capabilities such as product inventory and order management, recommendation system, and checkout function. This made me curious as to how much effort it would take to complete a retail application migration from an on-premise to cloud native solution.
The original architecture for this sample app looked like the below diagram.
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I’ve been working with distributed systems, platforms, and databases for the last seven years. Back in 2015, many architects began using distributed databases to scale beyond the boundaries of a single machine or server. They selected such a database for its horizontal scalability, even if its performance remained comparable to a conventional single-server database.
Now, with the rise of cloud native applications and serverless architecture, distributed databases need to do more than provide horizontal scalability.
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In the first post in this series, we covered how to secure YugabyteDB’s internal RPC protocol using the TLS encryption protocol, also referred to as server-to-server encryption in transit. In this post, we secure the communication between SQL clients and the PostgresQL query interface of YugabyteDB, also called client-to-server encryption in transit.
YugabyteDB—a 100% open source, distributed SQL database built to accelerate cloud native agility—stores important user and customer data at an organization.
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ybio is a PL/pgSQL based load generator for PostgreSQL and YSQL. This YugabyteDB-specific IO testing toolkit performs flexible IO testing to specific parts of the YugabyteDB infrastructure with no client installation. And because this toolkit is PL/pgSQL-based, it can also work on native PostgreSQL.
ybio is strongly inspired by Kevin Closson’s SLOB and pgio. Yugabyte Developer Advocate Franck Pachot took pgio and turned it into ybio.
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YugabyteDB is a 100% open source, distributed SQL database system. This single phrase expresses two distinct notions: a SQL database system, and a distributed database system. Historically, these notions were mutually exclusive. But current technology allows a single system to implement both notions. YugabyteDB does this with its two-layer architecture: an extensible query processing layer and a distributed document store.
In this blog post, we explain how YugabyteDB’s two-layer architecture works and compare it against other popular databases.
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Last November, we announced the general availability of YugabyteDB 2.11, a major release which extends PostgreSQL compatibility of the open source distributed SQL database. All these features are readily available in this stable release for any production environment.
In addition to making these features GA, YugabyteDB 2.12 introduces several new capabilities and significant improvements towards seamless security and better manageability.
Building customer trust is a top priority at Yugabyte.
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