Distributed SQL offers greater scalability, availability, and geo-distribution of data compared to PostgreSQL, but it is important to understand the differences in behaviors between the two systems in order to make the most of your distributed SQL database.
YugabyteDB uses LSM Tree / SST Files to minimize the risk of data corruption, in contrast to PostgreSQL’s method. This approach, coupled with independent compactions and checksum verification, enhances data integrity.
Discover how to best achieve high availability and disaster recovery using two data centers. This blog compares traditional monolithic databases with distributed SQL, and then discusses how it is all possible using YugabyteDB with cross-cluster replication capabilities.
See how how easy it is to use YugabyteDB Voyager to migrate a Node.js application backed by a single-node PostgreSQL database to a distributed YugabyteDB database cluster.
Every SQL execution in PostgreSQL and therefore in YugabyteDB YSQL takes time to process. A common way to identify how much is time spent on processing is to use the pg_stat_statements view in the database. However, the time visible in pg_stat_statements might differ from the time a database client registers for the execution. Where does this difference come from? Let’s take a look.
Learn how to best use Query Planner hints in the YugabyteDB database to optimize business queries based on how applications expose them. Walk through a use case that utilizes data sets from two popular TV shows to find total viewership per season, episode, etc.
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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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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