A SQL dashboard is a powerful tool that allows you to visualize data stored in a database such as MySQL, PostgreSQL or Snowflake. These dashboard tools require you to use SQL (Structured Query Language) to select the specific data (in a database) you wish to visualize.
Amazon DynamoDB is a fully managed NoSQL database service built for scalability and high performance. It’s one of the most popular databases used at SaaS companies, including Courier. We selected DynamoDB for the same reasons as everyone else: autoscaling, low cost, zero down time. However, at scale, DynamoDB can present serious performance issues.
PostgreSQL announced their latest version (PostgreSQL 14) on September 30th, which includes a bunch of features like pipeline API, gathering statistics on replication slots, query parallelism improvements and so on. While the origin of PostgreSQL can be traced back to 1986, it has been in active development for the past 30 years.
In this blog (Part III), we will discuss the motivation and high-level architecture of the DBaaS Backup and Recovery procedure for databases hosted on DBaaS. This blog discusses the motivations behind the Backup/Recovery process and it’s high-level design and architecture of the various components that constitute it.] These are the high-level motivations/goals for the Backup and Recovery design for DBaaS. There are two major design components.
Teams at Freshworks primarily use MySQL for their database needs. Freshworks being an AWS shop, RDS MySQL has been our primary, go-to solution. Sometime back a team was formed and tasked with building a self-hosted DB solution. We called ourselves the DBaaS (Database as a service) team and started with a DBaaS solution for MySQL. In this blog post (part I of the series) we discuss the motivation and high-level architecture of the DBaaS solution.