Explore how consensus-based replication gets implemented in distributed databases, and dive into Paxos and Raft, the most commonly used leader-based consensus protocols
YugabyteDB database has consistent, high-performance secondary indexes—built on top of distributed ACID transactions—to help retrieve data.
After billions of dollars in capital expenditure and reference customers in every major vertical, Google Cloud Platform has finally emerged as a credible competitor to Amazon Web Services and Microsoft Azure when it comes to enterprise-ready cloud infrastructure. While Google Cloud’s compute and storage offerings are easier to understand, making sense of its various managed database offerings is not for the faint-hearted. This post introduces app developers to the major Google Cloud database services,
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In this blog, we dive deeper into Percolator and Spanner as well as the open source databases (YugabyteDB for example) that they have inspired
First-generation NoSQL databases dropped ACID guarantees with the rationale that such guarantees are needed only by old-school enterprises running monolithic, relational applications in a single private data center. And the premise was that modern distributed apps should instead focus on linear database scalability along with low latency, mostly-accurate, single-key-only operations on shared-nothing storage (e.g. those provided by the public clouds).
Application developers who blindly accept the above reasoning are not serving their organizations well.
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Welcome to the inaugural edition of the YugabyteDB Community and Engineering update series! Let’s dive in and take a look at what has happened over the last few weeks.
DynamoDB is AWS’s NoSQL alternative to Cassandra, primarily marketed to mid-sized and large enterprises. It works best for those who require a flexible data model, reliable performance, and the automatic scaling of throughput capacity. In a nutshell, DynamoDB’s monthly cost is dictated by data storage, writes and reads. Let’s walk through a synopsis.
This post is to help developers and operations engineers understand the precise strengths and weaknesses of DynamoDB, especially when it needs to power a complex, large-scale application.
This post delves into the technical requirements of fast-growing geo-distributed applications with low latency reads and explores the limitations of Amazon DynamoDB for this use case, as well as alternative solutions such as MongoDB, Apache Cassandra, and YugabyteDB, a high-performance distributed SQL database.
Learn the basics of database storage engines, incl. B-tree and LSM tree based storage engines that are popular in the context of modern distributed cloud apps
