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Category: Google Spanner

Spanning the Globe without Google Spanner

Spanning the Globe without Google Spanner

Open Source Geo-Distributed Relational Database on Multi-Cluster Kubernetes

Google Spanner, conceived in 2007 for internal use in Google AdWords, has been rightly considered a marvel of modern software engineering. This is because it is the world’s first horizontally-scalable relational database that can be stretched not only across multiple nodes in a single data center but also across multiple geo-distributed data centers, without compromising ACID transactional guarantees.

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Distributed SQL Tips and Tricks – Feb 21, 2020

Distributed SQL Tips and Tricks – Feb 21, 2020

Welcome to this week’s tips and tricks blog where we recap some distributed SQL questions from around the Internet. We’ll also review upcoming events, new documentation, and blogs that have been published since the last post. Got questions? Make sure to ask them on our YugabyteDB Slack channel, Forum, GitHub, or Stackoverflow. Ok, let’s dive right in:

When should I use JSON vs JSONB data types?

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9 Techniques to Build Cloud-Native, Geo-Distributed SQL Apps with Low Latency

9 Techniques to Build Cloud-Native, Geo-Distributed SQL Apps with Low Latency

This post is an in-depth look at the various techniques that applications needing low latency and high availability can leverage while using a geo-distributed SQL database like YugabyteDB so that the negative impacts of a high-latency, unreliable Wide Area Network (WAN) are minimized.

Geo-Distributed SQL is the Future of RDBMS

Enterprises are increasingly moving to cloud native applications powered by microservices architecture. These applications run on elastic cloud infrastructure such as serverless frameworks and containers.

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2019 Distributed SQL Summit Recap and Highlights

2019 Distributed SQL Summit Recap and Highlights

Well, that’s a wrap! Yugabyte would like to extend a special thanks to JD and Amanda from the Postgreconf.org team, and to all the speakers from Facebook, Google, Amazon, Pivotal, Salesforce, Narvar, Plume Design and others that presented at the first-ever Distributed SQL Summit on Sept 20, 2019.

If you couldn’t make it out to this year’s event, have no fear!

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Achieving Fast Failovers After Network Partitions in a Distributed SQL Database

Achieving Fast Failovers After Network Partitions in a Distributed SQL Database

In February of this year, Kyle Kingsbury of Jepsen.io was conducting formal testing of YugabyteDB for correctness under extreme and unorthodox conditions. Obviously, simulating all manner of network partitions is part of his testing methodology. As a result, during his testing he spotted the fact that although nodes would reliably come back after a failure, the recovery itself was taking roughly 25 seconds to occur. We certainly didn’t like the sound of that!

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6 Technical Challenges Developing a Distributed SQL Database

6 Technical Challenges Developing a Distributed SQL Database

You can join the discussion on HackerNews here.

We crossed the three year mark of developing the YugabyteDB database in February of 2019. It has been a thrilling journey thus far, but not without its fair share of technical challenges. There were times when we had to go back to the drawing board and even sift through academic research to find a better solution than what we had at hand.

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Distributed PostgreSQL on a Google Spanner Architecture – Query Layer

Distributed PostgreSQL on a Google Spanner Architecture – Query Layer

Our previous post dived into the details of the storage layer of YugabyteDB called DocDB, a distributed document store inspired by Google Spanner. This post focuses on Yugabyte SQL (YSQL), a distributed, highly resilient, PostgreSQL-compatible SQL API layer powered by DocDB. A follow-up post will highlight the challenges faced and lessons learned when engineering such a database.

YSQL, Distributed PostgreSQL Made Real

Yugabyte SQL (YSQL) is a distributed and highly resilient SQL layer,

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Distributed PostgreSQL on a Google Spanner Architecture – Storage Layer

Distributed PostgreSQL on a Google Spanner Architecture – Storage Layer

In this post, we’ll dive into the architecture of the distributed storage layer of YugabyteDB, which is inspired by Google Spanner’s design. Our subsequent post covers the Query Layer, where the storage layer meets PostgreSQL as the SQL API. Finally, here is a follow-up post that highlights the key technical challenges we faced while engineering a distributed SQL database like YugabyteDB.

Logical Architecture

YugabyteDB is comprised of two logical layers,

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Rise of Globally Distributed SQL Databases – Redefining Transactional Stores for Cloud Native Era

Rise of Globally Distributed SQL Databases – Redefining Transactional Stores for Cloud Native Era

At last month’s KubeCon + CloudNativeCon in Seattle, the single biggest change from previous container-related conferences was the excitement among the end user companies around their adoption of Kubernetes and the associated cloud native infrastructure ecosystem. The CNCF End User Community page today lists 50+ enterprises and 21+ case studies including those from industry bellwethers such as Capital One, Netflix, Nordstrom and Pinterest. There is a common adoption pattern among all these case studies —

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Google Spanner vs. Calvin: Is There a Clear Winner in the Battle for Global Consistency at Scale?

Google Spanner vs. Calvin: Is There a Clear Winner in the Battle for Global Consistency at Scale?

Prof. Daniel Abadi, lead inventor of the Calvin transaction management protocol and the PACELC theorem, wrote a thought-provoking post last month titled “NewSQL database systems are failing to guarantee consistency, and I blame Spanner”. The post takes a negative view of software-only Google Spanner derivative databases such as YugabyteDB and CockroachDB that use Spanner-like partitioned consensus for single shard transactions and a two phase commit (2PC) protocol for multi-shard (aka distributed) ACID transactions.

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