Cloud Providers

Distributed SQL on Google Kubernetes Engine (GKE) with YugabyteDB’s Helm Chart

April 10, 2019

Distributed SQL Google Cloud Platform How To Kubernetes

Distributed SQL on Google Kubernetes Engine (GKE) with YugabyteDB’s Helm Chart

The glory days of the heavy-weight hypervisor are slowly fading away, and in the last few years, containerization of applications and services is the new reality. With containerization, enterprises can prototype, deploy, and meet scale demands more quickly. To systematically and efficiently manage these large-scale deployments, enterprises have bet on technologies like Kubernetes (aka k8s), a powerful container orchestrator, to get the job done. Kubernetes was originally developed by Google, but it has been open sourced since 2014 and is today developed by a large community of contributors.

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New to Google Cloud Databases? 5 Areas of Confusion That You Better Be Aware of

July 25, 2018

By Sid Choudhury

Google Cloud Platform Google Spanner

New to Google Cloud Databases? 5 Areas of Confusion That You Better Be Aware of

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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Implementing Distributed Transactions the Google Way: Percolator vs. Spanner

July 23, 2018

By Sid Choudhury

ACID Transactions CockroachDB Distributed SQL Google Cloud Platform Google Spanner

Implementing Distributed Transactions the Google Way: Percolator vs. Spanner

Our post 6 Signs You Might be Misunderstanding ACID Transactions in Distributed Databases describes the key challenges involved in building high performance distributed transactions. Multiple open source ACID-compliant distributed databases have started building such transactions by taking inspiration from research papers published by Google. In this post, we dive deeper into Percolator and Spanner, the two Google systems behind those papers, as well as the open source databases they have inspired.

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How DynamoDB’s Pricing Works, Gets Expensive Quickly and the Best Alternatives

July 18, 2018

By Jimmy Guerrero

Amazon DynamoDB Amazon Web Services

How DynamoDB’s Pricing Works, Gets Expensive Quickly and the Best Alternatives

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.

11 Things You Wish You Knew Before Starting with DynamoDB

July 10, 2018

By Karthik Ranganathan

Amazon DynamoDB Amazon Web Services

11 Things You Wish You Knew Before Starting with DynamoDB

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.

Achieving Sub-ms Latencies on Large Datasets in Public Clouds

January 26, 2018

By Kannan Muthukkaruppan

Amazon Web Services Cloud Providers Google Cloud Platform How It Works Microsoft Azure Performance Benchmarks

Achieving Sub-ms Latencies on Large Datasets in Public Clouds

One of our users was interested to learn more about YugabyteDB’s behavior for a random read workload where the data set does not fit in RAM and queries need to read data from disk (i.e. an uncached random read workload).

The intent was to verify if YugabyteDB was designed well to handle this case with the optimal number of IOs to the disk subsystem.

This post is a sneak peak into just one of the aspects of YugabyteDB’s innovative storage engine,

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Practical Tradeoffs in Google Cloud Spanner, Azure Cosmos DB and YugabyteDB

January 25, 2018

By Sid Choudhury

ACID Transactions Amazon Web Services Distributed SQL Google Cloud Platform Google Spanner Microsoft Azure Microsoft Azure Cosmos DB

Practical Tradeoffs in Google Cloud Spanner, Azure Cosmos DB and YugabyteDB

Updated April 2019.

The famed CAP Theorem has been a source of much debate among distributed systems engineers. Those of us building distributed databases are often asked how we deal with it. In this post, we dive deeper into the consistency-availability tradeoff imposed by CAP which is only applicable during failure conditions. We also highlight the lesser-known-but-equally-important consistency-latency tradeoff imposed by the PACELC Theorem that extends CAP to normal operations.

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August 18, 2017

By Karthik Ranganathan

Cloud Providers Databases

NoSQL vs SQL in 2017

Came across the image below here and this made me smile. Not because of the implied complexity of choosing a database, but the reality with which this flow chart captures the state of the database world today in 2017. Of course, running whatever database you end up choosing in production is a whole another order of complexity.

I have been working on distributed systems for the last 10+ years.

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Cloud Providers

Explore Distributed SQL and YugabyteDB in Depth