Implementing Distributed Transactions the Google Way: Percolator vs. Spanner
In this blog, we dive deeper into Percolator and Spanner as well as the open source databases (YugabyteDB for example) that they have inspired
July 23, 2018
Search: yugabyte intern
July 22, 2018
6 Signs You Might be Misunderstanding ACID Transactions in Distributed Databases
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.
…
June 28, 2018
A Busy Developer’s Guide to Database Storage Engines — The Basics
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
April 24, 2018
Distributed ACID Transactions with High Performance
ACID transactions are a fundamental building block when developing business-critical, user-facing applications. They simplify the complex task of ensuring data integrity while supporting highly concurrent operations. While they are taken for granted in monolithic SQL/relational databases, distributed NoSQL/non-relational databases either forsake them completely or support only a highly restrictive single-row flavor (see sections below). This loss of ACID properties is usually justified with a gain in performance (measured in terms of low latency and/or high throughput).
…
January 26, 2018
Amazon Web ServicesCloud ProvidersGoogle Cloud PlatformHow It WorksMicrosoft AzurePerformance 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,
…
January 5, 2018
Extending Redis API with a Native Time Series Data Type
This blog highlights the challenges of handling time series data with vanilla Redis and the efficiency of YugaByte’s TS datatype
August 29, 2017
Facebook’s User Database — Is it SQL or NoSQL?
Ever wondered which database Facebook (FB) uses to store the profiles of its 2.3B+ users? Is it SQL or NoSQL? How has FB database architecture evolved over the last 15+ years? As an engineer in FB database infrastructure team from 2007 to 2013, I had a front row seat in witnessing this evolution. There are invaluable lessons to be learned by better understanding the database evolution at the world’s largest social network,
…