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How to Build a Scalable Tech Stack for a Growing SaaS Product

There is a wealth of advice available to early-stage SaaS startups (or any other business developing a new Growing SaaS Product) regarding the importance of identifying the correct clients and markets to serve.

Product-market fit is usually viewed as the main cause of new product failure. However, there is little guidance available to those who survive or live longer on how to choose and construct a scalable technical stack that will sustain their product and customers in the long run.

The majority of early-stage companies largely rely on the Minimum Viable Product (MVP) practice, which enables them to iterate more quickly while determining client demands. In many cases, the MVP is a collection of scripts and UI components that are swiftly assembled in order to test new features and collect client feedback.

Once businesses reach product-market fit, they invest in developing a scalable and secure product. The issue with this method is that it results in a considerable disconnect between the state of the MVP and the need for a great future product. If the business is well capitalized, this gap is generally easy to close, albeit slowly. However, if it is self-sustaining with little outside funding, this task becomes considerably more difficult.

The Database

At the heart of each modern SaaS product’s technology stack is a dependable, secure, and scalable database. This component is critical to the long-term success of your product, and any errors made in selecting and designing your database will incur considerable costs to rectify. 

When it comes to selecting a database for your new Growing SaaS Product, there are various considerations. I’ll walk you through each one below.

Self-Managed vs Fully Managed

Self-managed databases give you complete freedom, allowing you to create a database that is tailored to your specific requirements while avoiding cloud vendor lock-in. You will deploy, configure, and maintain your database on cloud servers from the start. This is typically the less expensive choice, particularly at scale. This comes at a cost, as you will require the necessary time, resources, and talents.

If they are in short supply, you may want to explore a fully-managed database, which is often offered as a service by the majority of cloud vendors. It is significantly simpler to configure, deploy, and scale, as the vendor will handle these tasks for you behind the scenes. However, they are typically more expensive and offer limited customization and adaptability to meet individual demands.

More in-depth studies of the two alternatives may be found here and here.

SQL vs NoSQL

The SQL vs. NoSQL argument has raged on for over a decade, dating all the way back to the inception of NoSQL databases. The reality is that there is no single answer. It varies according to your product, the type of data being handled, and the manner in which the product interacts with the data.

SQL databases are built with data normalization and ACID in mind. They make better use of resources and are designed with data integrity in mind. Additionally, as their name implies, they make use of a common query language, which simplifies data access. Their primary shortcoming is the rigidity of their data structures and their inability to scale horizontally, although considerable progress has been made recently on the scaling front.

On the other hand, NoSQL databases enable flexible data models natively and can readily scale horizontally, however they do so by foregoing (part of) the ACID constraints and the traditional query language.

Open source vs. proprietary

Over the last decade, open-source databases have gained substantial traction. Meanwhile, the appeal of commercial databases has dwindled. While the latter is still commonly utilized in large enterprises (banks, government agencies, and insurance firms, for example), the majority of new saas application development company are mainly reliant on open-source software. Cost, availability, independence, and a sense of community all contribute to this choice.

Multi-tenancy

Assuming the product is used by more than one consumer, it must be designed to support numerous customers or renters. Each tenant typically consists of one or more users from the same organization interacting with the product.

In a multi-tenant SaaS architecture, multiple clients share a single instance of the application. Benefits include cheaper operating expenses, improved resource use, and ease of maintenance and update. There are several patterns for designing a database configuration and data model for multi-tenant architecture.

One database per tenant

This technique allocates a separate database to each tenant, despite the fact that they share the same app instance. This occurs upon user authentication. Cost savings through sharing database and computer resources.

Single multi-tenant database

This technique consolidates tenant data into a single multi-tenant database. This method is less expensive but increases tenant isolation. The structure of a multi-tenant database should include tenant identifier fields to enable secure data retrieval for each tenant. 

This complicates the design of the database and application logic. Additionally, due to the shared nature of database storage and computational resources, performance bottlenecks are more likely to emerge when a large number of tenants are particularly active concurrently.

Sharded multi-tenant databases

This pattern combines the previous two. No, tenant data is not shared. Although it is a viable alternative to a single multi-tenant database, it adds complexity to both the database design and application logic. Centralize tenant and database tracking (which tenant goes to which database).

It’s best to use multi-tenant database architectures when the target market is large and willing to pay (i.e. freelancers, SMEs).In this instance, your data model must be capable of supporting a big number of renters cost-effectively.

User authentication

Identity management is a required and complicated component of every Growing SaaS Product offering, with substantial implications for the availability and security of your product. You have two options: do it yourself or hire a provider. Although authentication appears to be straightforward to perform at first glance, it is difficult to execute correctly. It entails a great deal more than simply maintaining a table containing user names and password entries. 

Must incorporate strong encryption, anomaly detection, and vulnerability management, to name a few. A lot may go wrong, and when they do, your reputation suffers. Depending on your clients’ needs, you may also need to support multi-factor authentication or social and enterprise identity providers.

Build a stack that fuels your business growth

Whether you have achieved product-market fit or not, you must continue to listen to your customers’ demands and provide value. You can either improvise features or design an integrated solution that works for you.

The technical stack of a scalable and secure SaaS service is complicated, requiring numerous components to function together. To architect and construct a strong stack, the business must progress beyond the Minimum Viable Product (MVP) phase while maintaining the same level of speed and agility.

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