- [Some study on database storage internals](https://medium.com/@kousiknath/data-structures-database-storage-internals-1f5ed3619d43)
- [Sharding Pinterest: How we scaled our MySQL fleet](https://medium.com/@Pinterest_Engineering/sharding-pinterest-how-we-scaled-our-mysql-fleet-3f341e96ca6f)
- [Guide to MySQL High Availability](https://www.mysql.com/cn/why-mysql/white-papers/mysql-guide-to-high-availability-solutions/)
- [Choosing MySQL High Availability Solutions](https://dzone.com/articles/choosing-mysql-high-availability-solutions)
- [High availability with MariaDB TX: The definitive guide](https://mariadb.com/sites/default/files/content/Whitepaper_High_availability_with_MariaDB-TX.pdf)
- Mysql 相关经验
- [Booking.com: Evolution of MySQL System Design](https://www.percona.com/live/mysql-conference-2015/sessions/bookingcom-evolution-mysql-system-design) ，Booking.com 的 MySQL 数据库使用的演化，其中有很多不错的经验分享，我相信也是很多公司会遇到的的问题。
- [Tracking the Money-Scaling Financial Reporting at Airbnb](https://medium.com/airbnb-engineering/tracking-the-money-scaling-financial-reporting-at-airbnb-6d742b80f040) ，Airbnb 的数据库扩展的经验分享。
- [Why Uber Engineering Switched from Postgres to MySQL](https://eng.uber.com/mysql-migration/) ，无意比较两个数据库谁好谁不好，推荐这篇 Uber 的长文，主要是想让你从中学习到一些经验和技术细节，这是一篇很不错的文章。
- Mysql 集群复制
- [Monitoring Delayed Replication, With A Focus On MySQL](https://engineering.imvu.com/2013/01/09/monitoring-delayed-replication-with-a-focus-on-mysql/)
- [Mitigating replication lag and reducing read load with freno](https://githubengineering.com/mitigating-replication-lag-and-reducing-read-load-with-freno/)
- [Better Parallel Replication for MySQL](https://medium.com/booking-com-infrastructure/better-parallel-replication-for-mysql-14e2d7857813)
- [Evaluating MySQL Parallel Replication Part 2: Slave Group Commit](https://medium.com/booking-com-infrastructure/evaluating-mysql-parallel-replication-part-2-slave-group-commit-459026a141d2)
- [Evaluating MySQL Parallel Replication Part 3: Benchmarks in Production](https://medium.com/booking-com-infrastructure/evaluating-mysql-parallel-replication-part-3-benchmarks-in-production-db5811058d74)
- [Evaluating MySQL Parallel Replication Part 4: More Benchmarks in Production](https://medium.com/booking-com-infrastructure/evaluating-mysql-parallel-replication-part-4-more-benchmarks-in-production-49ee255043ab)
- [Evaluating MySQL Parallel Replication Part 4, Annex: Under the Hood](https://medium.com/booking-com-infrastructure/evaluating-mysql-parallel-replication-part-4-annex-under-the-hood-eb456cf8b2fb)
- Mysql 数据分区
- [StackOverflow: MySQL sharding approaches?](https://stackoverflow.com/questions/5541421/mysql-sharding-approaches)
- [Why you don’t want to shard](https://www.percona.com/blog/2009/08/06/why-you-dont-want-to-shard/)
- [How to Scale Big Data Applications](https://www.percona.com/sites/default/files/presentations/How to Scale Big Data Applications.pdf)
- [MySQL Sharding with ProxySQL](https://www.percona.com/blog/2016/08/30/mysql-sharding-with-proxysql/)
- 各公司的 Mysql 数据分区经验分享
- [MailChimp: Using Shards to Accommodate Millions of Users](https://devs.mailchimp.com/blog/using-shards-to-accommodate-millions-of-users/)
- [Uber: Code Migration in Production: Rewriting the Sharding Layer of Uber’s Schemaless Datastore](https://eng.uber.com/schemaless-rewrite/)
- [Sharding & IDs at Instagram](https://instagram-engineering.com/sharding-ids-at-instagram-1cf5a71e5a5c)
- [Airbnb: How We Partitioned Airbnb’s Main Database in Two Weeks](https://medium.com/airbnb-engineering/how-we-partitioned-airbnb-s-main-database-in-two-weeks-55f7e006ff21)
- **更多资源**
- [awesome-mysql](https://github.com/jobbole/awesome-mysql-cn) - MySQL 的资源列表
- [NoSQL Databases: a Survey and Decision Guidance](https://medium.com/baqend-blog/nosql-databases-a-survey-and-decision-guidance-ea7823a822d#.nhzop4d23)，这篇文章可以带你自上而下地从 CAP 原理到开始了解 NoSQL 的种种技术，是一篇非常不错的文章。
- [Distribution, Data, Deployment: Software Architecture Convergence in Big Data Systems](https://resources.sei.cmu.edu/asset_files/WhitePaper/2014_019_001_90915.pdf)，这是卡内基·梅隆大学的一篇讲分布式大数据系统的论文。其中主要讨论了在大数据时代下的软件工程中的一些关键点，也说到了 NoSQL 数据库。
- [No Relation: The Mixed Blessings of Non-Relational Databases](http://ianvarley.com/UT/MR/Varley_MastersReport_Full_2009-08-07.pdf)，这篇论文虽然有点年代久远。但这篇论文是 HBase 的基础，你花上一点时间来读读，就可以了解到，对各种非关系型数据存储优缺点的一个很好的比较。
- 因为 CAP 原理，所以当你需要选择一个 NoSQL 数据库的时候，你应该看看这篇文档 [Visual Guide to NoSQL Systems](http://blog.nahurst.com/visual-guide-to-nosql-systems)。
选 SQL 还是 NoSQL，这里有两篇文章，值得你看看。
- [SQL vs. NoSQL Databases: What’s the Difference?](https://www.upwork.com/hiring/data/sql-vs-nosql-databases-whats-the-difference/)
- [Salesforce: SQL or NoSQL](https://engineering.salesforce.com/sql-or-nosql-9eaf1d92545b)
### 列式数据库资料
#### Cassandra 资料
- 沃尔玛实验室有两篇文章值得一读。
- [Avoid Pitfalls in Scaling Cassandra Cluster at Walmart](https://medium.com/walmartlabs/avoid-pitfalls-in-scaling-your-cassandra-cluster-lessons-and-remedies-a71ca01f8c04)
- [Storing Images in Cassandra at Walmart](https://medium.com/walmartlabs/building-object-store-storing-images-in-cassandra-walmart-scale-a6b9c02af593)
- [Yelp: How We Scaled Our Ad Analytics with Apache Cassandra](https://engineeringblog.yelp.com/2016/08/how-we-scaled-our-ad-analytics-with-cassandra.html) ，Yelp 的这篇博客也有一些相关的经验和教训。
- [Discord: How Discord Stores Billions of Messages](https://blog.discordapp.com/how-discord-stores-billions-of-messages-7fa6ec7ee4c7) ，Discord 公司分享的一个如何存储十亿级消息的技术文章。
- [Netflix: Benchmarking Cassandra Scalability on AWS-Over a million writes per second](https://medium.com/netflix-techblog/benchmarking-cassandra-scalability-on-aws-over-a-million-writes-per-second-39f45f066c9e) ，Netflix 公司在 AWS 上给 Cassandra 做的一个 Benchmark。
#### HBase 资料
- [Imgur Notification: From MySQL to HBASE](https://medium.com/imgur-engineering/imgur-notifications-from-mysql-to-hbase-9dba6fc44183)
- [HBase File Locality in HDFS](http://www.larsgeorge.com/2010/05/hbase-file-locality-in-hdfs.html)
- [Apache Hadoop Goes Realtime at Facebook](http://borthakur.com/ftp/RealtimeHadoopSigmod2011.pdf)
- [Storage Infrastructure Behind Facebook Messages: Using HBase at Scale](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.294.8459&rep=rep1&type=pdf)
- [Learn Redis the hard way (in production) at Trivago](http://tech.trivago.com/2017/01/25/learn-redis-the-hard-way-in-production/)
- [Twitter: How Twitter Uses Redis To Scale - 105TB RAM, 39MM QPS, 10,000+ Instances](http://highscalability.com/blog/2014/9/8/how-twitter-uses-redis-to-scale-105tb-ram-39mm-qps-10000-ins.html)
- [Slack: Scaling Slack’s Job Queue - Robustly Handling Billions of Tasks in Milliseconds Using Kafka and Redis](https://slack.engineering/scaling-slacks-job-queue-687222e9d100)
- [GitHub: Moving persistent data out of Redis at GitHub](https://githubengineering.com/moving-persistent-data-out-of-redis/)
- [Instagram: Storing Hundreds of Millions of Simple Key-Value Pairs in Redis](https://engineering.instagram.com/storing-hundreds-of-millions-of-simple-key-value-pairs-in-redis-1091ae80f74c)
- [Redis in Chat Architecture of Twitch (from 27:22)](https://www.infoq.com/presentations/twitch-pokemon)
- [Deliveroo: Optimizing Session Key Storage in Redis](https://deliveroo.engineering/2016/10/07/optimising-session-key-storage.html)
- [Introduction to MongoDB](https://www.slideshare.net/mdirolf/introduction-to-mongodb)
- [eBay: Building Mission-Critical Multi-Data Center Applications with MongoDB](https://www.mongodb.com/blog/post/ebay-building-mission-critical-multi-data-center-applications-with-mongodb)
- [The AWS and MongoDB Infrastructure of Parse: Lessons Learned](https://medium.baqend.com/parse-is-gone-a-few-secrets-about-their-infrastructure-91b3ab2fcf71)
- [Migrating Mountains of Mongo Data](https://medium.com/build-addepar/migrating-mountains-of-mongo-data-63e530539952)
- [Intro to graph databases, Part 1, Graph databases and the CRUD operations](https://www.ibm.com/developerworks/library/cl-graph-database-1/cl-graph-database-1-pdf.pdf)
- [Intro to graph databases, Part 2, Building a recommendation engine with a graph database](https://www.ibm.com/developerworks/library/cl-graph-database-2/cl-graph-database-2-pdf.pdf)
- [Handling Billions of Edges in a Graph Database](https://www.infoq.com/presentations/graph-database-scalability)
- [Neo4j case studies with Walmart, eBay, AirBnB, NASA, etc](https://neo4j.com/customers/)
- [FlockDB: Distributed Graph Database for Storing Adjacency Lists at Twitter](https://blog.twitter.com/engineering/en_us/a/2010/introducing-flockdb.html)
- [JanusGraph: Scalable Graph Database backed by Google, IBM and Hortonworks](https://architecht.io/google-ibm-back-new-open-source-graph-database-project-janusgraph-1d74fb78db6b)
- [What is Time-Series Data & Why We Need a Time-Series Database](https://blog.timescale.com/what-the-heck-is-time-series-data-and-why-do-i-need-a-time-series-database-dcf3b1b18563)
- [Time Series Data: Why and How to Use a Relational Database instead of NoSQL](https://blog.timescale.com/time-series-data-why-and-how-to-use-a-relational-database-instead-of-nosql-d0cd6975e87c)
- [Beringei: High-performance Time Series Storage Engine @Facebook](https://code.facebook.com/posts/952820474848503/beringei-a-high-performance-time-series-storage-engine/)
- [Building a Scalable Time Series Database on PostgreSQL](https://blog.timescale.com/when-boring-is-awesome-building-a-scalable-time-series-database-on-postgresql-2900ea453ee2)
- [Scaling Time Series Data Storage - Part I @Netflix](https://medium.com/netflix-techblog/scaling-time-series-data-storage-part-i-ec2b6d44ba39)
- [Design of a Cost Efficient Time Series Store for Big Data](https://medium.com/@leventov/design-of-a-cost-efficient-time-series-store-for-big-data-88c5dc41af8e)
