August 2024 Summaries

Budibase and YugabyteDB can be combined to build a robust low code/no code app, enabling business users to streamline operations, reduce costs, and achieve faster time-to-market. Budibase's intuitive drag-and-drop interface democratizes app development, while its flexibility supports integrations with various data sources, including YugabyteDB. YugabyteDB provides a scalable and reliable backend that ensures high availability, horizontal scalability, and strong consistency, making it an ideal partner for Budibase. By leveraging this combination, organizations can efficiently solve complex challenges, ensuring scalability, reliability, and seamless global data distribution. Potential use cases include metadata correction in a data lake, e-commerce order tracking, and survey and feedback applications, which can be rapidly addressed with low-code/no-code development.

We are proud to be the only distributed database with enhanced PostgreSQL compatibility, which means that an app that runs on Postgres will work on YugabyteDB with minimal changes, while tapping into the built-in scalability and resilience of a distributed architecture. We aim to prove this claim by migrating 100 popular open source Postgres applications to YugabyteDB as part of the Postgres App Century Challenge, and we invite developers to join us in this effort by exploring our repo with the list of apps to migrate, picking an app, running it on Postgres, and then migrating it to YugabyteDB, documenting their experience along the way. By participating, contributors will receive exclusive brag-worthy swag, effusive praise, and the opportunity to work on a cool project that tests the limits of YugabyteDB's Postgres compatibility.

The viability of open source as a long-term business model is being questioned with Cockroach Labs' recent licensing change, which eliminates its free Core offering and requires users making over $10m in revenue to pay for the proprietary Enterprise license. This move may stifle long-term growth and kill the growth engine by adding friction for businesses considering adopting the database. The trend of restricting core access and features is seen in other former open-source projects, such as MongoDB, Confluent, Elastic, Redis Labs, and others. In contrast, a company like YugabyteDB has successfully adopted an open source model, with over 10,000 users and millions of deployments, and reaffirms its commitment to open source under the Apache 2.0 license. The open source model remains one of the most successful approaches to developing and distributing business-critical infrastructure software, offering exponential adoption growth and strategic optionality for customers. PostgreSQL is expected to continue as a popular and widely-supported open-source database, with YugabyteDB providing runtime compatibility and inheriting its vast ecosystem of integrations.

This blog demonstrates the deployment of a high-performance multi-region application on Google Cloud using Apigee and YugabyteDB. It shows how to achieve low-latency reads and writes across multiple cloud regions by leveraging Apigee's API management capabilities and YugabyteDB's distributed database design patterns, including geo-partitioning and global database with follower reads. The example application, YugaMovies, uses a multi-region YugabyteDB cluster and Apigee instances to provide fast and secure access to movie recommendations for users worldwide.

YugabyteDB is a distributed SQL database that delivers high-performance and scalable solutions, backed by rigorous testing and validation across various benchmarks and tools. The company's engineering team leverages these tests to ensure the robustness and operational capabilities of YugabyteDB, including performance, scalability, transactional consistency, high availability, and PostgreSQL compatibility. Standard performance tests, such as TPCC and Sysbench, are run nightly to verify basic operational capabilities, while microbenchmarks test specific database operations in isolation. Scalability testing ensures that the database can handle increasing workloads without compromising performance, with multi-region tests simulating a global deployment and scale-in and scale-out performance tests measuring the impact of scaling operations on latencies. Large-scale stress tests using TPCC benchmarks validate high-load scenarios, while cluster operations testing evaluates the impact of maintenance and management operations on performance.