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
June 28, 2018
Databases
June 28, 2018
A Busy Developer’s Guide to Database Storage Engines — Advanced Topics
In the first post of this two-part series, we learned about the B-tree vs LSM approach to index management in operational databases. While the indexing algorithm plays a fundamental role in determining the type of storage engine needed, advanced considerations highlighted below are equally important to consider.
Consistency, Transactions, and Concurrency Control
Monolithic databases, which are primarily relational/SQL in nature, support strong consistency and ACID transactions.
…
June 11, 2018
Docker, Kubernetes and the Rise of Cloud Native Databases
Containerized Stateful Services Are Here
Results from the 2018 Kubernetes Application Usage Survey should put to rest concerns enterprise users have had around the viability of Docker containers and Kubernetes orchestration for running stateful services such as databases and message queues. Its exciting to see that nearly 40% of respondents are running databases (SQL and/or NoSQL) using Kubernetes. This number will continue to grow in the months ahead.
…
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).
…
March 7, 2018
Overcoming MongoDB Sharding and Replication Limitations
MongoDB’s sharding and replication have improved since it was first an AP database, but it still has limitations for highly scalable and latency-sensitive apps. In this blog, the authors discuss why users switch to YugabyteDB due to distributed ACID transactions and improved scalability.
January 25, 2018
ACID TransactionsAmazon Web ServicesDistributed SQLGoogle Cloud PlatformGoogle SpannerMicrosoft AzureMicrosoft 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.
…
December 20, 2017
Building a Strongly Consistent Cassandra with Better Performance
In an earlier blog on database consistency, we had a detailed discussion on the risks and challenges applications face in dealing with eventually consistent NoSQL databases. We also dispelled the myth that eventually consistent DBs perform better than strongly consistent DBs. In this blog, we will look more closely into how YugabyteDB provides strong consistency while outperforming an eventually consistent DB like Apache Cassandra. Note that YugabyteDB retains drop-in compatibility with the Cassandra Query Language (CQL) API.
…
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,
…