We use postgresql for the merge between sql/nosql. A lot of our data is unstructured JSON, or JSON that is currently in flux due to some MVP/interation processes that are going on. PostgreSQL gives the capability to do this.

At the moment PostgreSQL on amazon is only at 9.5 which is one minor version down from support for document fragment updates which is something that we are waiting for. However, that may be some ways away.

Other than that, we are using PostgreSQL as our main SQL store as a replacement for all the MSSQL databases that we have. Not only does it have great support through RDS (small ops team), but it also has some great ways for us to migrate off RDS to managed EC2 instances down the line if we need to.

PostgreSQL combines the best aspects of traditional SQL databases such as reliability, consistent performance, transactions, querying power, etc. with the flexibility of schemaless noSQL systems that are all the rage these days. Through the powerful JSON column types and indexes, you can now have your cake and eat it too! PostgreSQL may seem a bit arcane and old fashioned at first, but the developers have clearly shown that they understand databases and the storage trends better than almost anyone else. It definitely deserves to be part of everyone's toolbox; when you find yourself needing rock solid performance, operational simplicity and reliability, reach for PostgresQL.

Relational data stores solve a lot of problems reasonably well. Postgres has some data types that are really handy such as spatial, json, and a plethora of useful dates and integers. It has good availability of indexing solutions, and is well-supported for both custom modifications as well as hosting options (I like Amazon's Postgres for RDS). I use HoneySQL for Clojure as a composable AST that translates reliably to SQL. I typically use JDBC on Clojure, usually via org.clojure/java.jdbc.

PostgreSQL is responsible for nearly all data storage, validation and integrity. We leverage constraints, functions and custom extensions to ensure we have only one source of truth for our data access rules and that those rules live as close to the data as possible. Call us crazy, but ORMs only lead to ruin and despair.

Tried MongoDB - early euphoria - later dread. Tried MySQL - not bad at all. Found PostgreSQL - will never go back. So much support for this it should be your first choice. Simple local (free) installation, and one-click setup in Heroku - lots of options in terms of pricing/performance combinations.

Aside from Redis, we use MariaDB to store long-term information like user-data and big-data like regeneration-information for our open-world servers. We extensively use the relational aspects of MariaDB in joins, nested queries and unions.

mysql보다 mariaDB가 join면에서 우수하다는 문서를 읽었습니다. 이 부분은 저의 블로그에서도 다뤘고 저의 word press 블로그는 mysql 대신 mariaDB 를 사용합니다.

특히 limit 기능이 pagenation 처리를 할 때 너무 직관적이고 편해서 mariaDB, mysql을 사랑합니다.

Introduced in computer science course.managing relational database management systems, database analytics, and for data processing

수 백만개가 넘는 태그 키워드의 자동완성을 위해서 별도의 데이터베이스를 구축하였습니다. MariaDB 는 MySQL 을 포크한 프로젝트입니다. MySQL 과의 강력한 호환성을 지니며, 큰 튜닝 없이 강력한 성능을 보장합니다.

MariaDB has allowed us to easily scale out our DB cluster. Also has better replication tools than MySQL