MongoDB compatibility has been added to the Tigris open source NoSQL database and search platform and is now also available on Tigris Cloud.
The first beta release of Tigris MongoDB compatibility offers support for MongoDB 6.0+ CRUD and Aggregation operations. Any application that uses the supported MongoDB CRUD and Aggregation operations, no matter the programming language, can now use Tigris instead of a self-hosted MongoDB instance or MongoDB Atlas.
This is part 2 of the NoSQL Data Modeling Series. In the first part of the series, we covered modeling NoSQL one-to-one relations. In this second part of the series, we will explore modeling NoSQL one-to-many relations. We'll look at two ways to implement NoSQL one-to-many relations. The first uses an embedded NoSQL design pattern, and the second uses a separate collection with a relation field. We will also look at when it is best to use either of these designs.
We are running FoundationDB with the official kubernetes operator.
FoundationDB supports logical backups (with backup_agent) and disaster recovery (with dr_agent) through copying
the database/streaming changes logically. It also supports binary backups through disk snapshots.
In this blog post, we will describe how to make a backup of FoundationDB via backup_agent. The FoundationDB operator
supports making logical backups via backup_agent, but it does not support running DR with dr_agent. We decided to run backup_agent
as a separate deployment to allow a symmetric setup with dr_agent.
Tigris provides a transactional NoSQL document database, this allows you to create NoSQL data models representing relations in a few different ways to get the best performance, consistency and ease of use in your application.
In this blog, I show you how to model NoSQL one-to-one relationships using the embedded document and sub-document NoSQL design pattern. We'll get hands-on with Tigris to achieve this, however the NoSQL data modeling design patterns are applicable to other NoSQL databases. We will combine this with Tigris's transactions to make sure that all updates are consistent. I will show how to model NoSQL one-to-many and NoSQL many-to-many relationships in future posts as part of the NoSQL Data Modeling Series.
Tigris is a Serverless NoSQL Database and Search Platform that offers a modern open source alternative to MongoDB and DynamoDB. Tigris utilizes FoundationDB's transactional key-value interface as its underlying storage engine. In a blog post titled How We Built the Data Layer on FoundationDB, we delved into why we decided to use FoundationDB for this purpose. This blog focuses on the serializable transactions provided by Tigris and compares it to transactions in MongoDB.
As we continue to build out our open source Developer Data Platform with data services such as Database and Search, we're constantly exploring ecosystems and their technologies to determine where our platform solves the biggest problems and is the best fit.
tRPC and Next.js standout in the serverless ecosystem. tRPC's mission of enabling developers to move fast and break nothing via end-to-end typesafe APIs perfectly aligns with our thinking at Tigris Data. In particular, how Tigris Database enables developers to define their data models in TypeScript and use them throughout their application logic, on both client and server.
So, in this tutorial series, we'll build a micro-blogging application called "Stream Social" using Tigris Database, Tigris Search, tRPC, and Next.js.
Tigris is a production-grade platform built to handle large datasets and a high volume of reads and writes. So, we'll pre-load the application with a reasonable sample size of 10,000 posts across a number of different users. We'll build functionality that lists the posts and allows you to paginate through them. We'll also add the ability to view all posts from a specific user and perform full-text search on all the posts.
In the previous blog post
we discussed using Tigris as a scalable, cost-effective, and open source
alternative to MongoDB Atlas. As a continuation of that, this blog post will
demonstrate using the MongoDB Shell mongosh
in a way that is transparent to the application that the data is stored in
Tigris Cloud database.
Furthermore, there will be no cluster to create and no sharding to worry about.
We have also recorded a video if you prefer video content.
MongoDB is one of the most popular databases developers use for data persistence for their applications. MongoDB has several benefits over traditional relational databases. One of the most significant advantages is its flexible data model, which makes it easier for developers to manage their data.
MongoDB Atlas is the cloud-hosted version of MongoDB, including other proprietary data services such as Search and Analytics. While Atlas provides several benefits, there are three major issues associated with it: costs, control over data, and operational issues when dealing with large datasets.
In this blog post, we discuss Tigris as a scalable, cost-effective, and open source alternative to MongoDB Atlas. We will also demonstrate using Go driver for MongoDB in a way that is transparent to the application that the data is stored in Tigris Cloud database.
The Tigris Go MongoDB quickstart code is available on GitHub.
Real-time full-text search is a feature that enhances the user experience of web applications, particularly in online stores, social media platforms, documentation, and blogs. It enables users to search and instantly get up-to-date information returned to them. Combining that with an experience where search results update as a user types (without direct user query submission or a page reload) provides an even better UX that helps users get the information they need more efficiently.
In this tutorial, we'll walk you through converting a static Next.js e-commerce product listing into a database-driven site with real-time full-text search of all products using Tigris.
In the following section, we'll provide background info on real-time, full-text search, and how Tigris is an enabler of both. However, feel free to jump to the Tutorial to follow the step-by-step guide. Or, head to the real-time full-text search GitHub repo if you want to dive into the code.
We've just published a new guide in our documentation covering how to Add Full-Text Search to a Nuxt E-commerce Store with Tigris Search & Netlify Functions.
