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Why Your Enterprise Needs a Schema-Free Database

Interior of server room

Schema-free databases are designed to offer unmatched flexibility and scalability—here’s why you need one in your enterprise.

Today’s enterprises are responsible for collecting and managing more data than ever before—and it wouldn’t be possible without databases. Simply put, databases are stores of information that are organized so tech teams can easily access, manage, and update them. Databases can store anything from files to sales transactions to digital information about your customers.

Databases have evolved quite a bit since their creation in the 1960s. In addition to the tried-and-true relational database, we now have object-oriented, cloud, graph, SQL, and NoSQL databases. Which type is best for your enterprise? Hint: it’s not the one you’re thinking. Here’s everything else you need to know about schema-free or schemaless databases, including why your enterprise needs one.

What is a schema-free database?

Ever since the 1980s and 1990s, the vast majority of databases used by tech teams are organized according to schemas. Schemas, typically written in SQL, are sets of enforceable rules about a database’s structure. They describe and define every functional element including tables, indexes, and relationships. In short, schemas normalize and regulate all data that goes into the database.

Let’s say your relational database defines a customer record as a customer ID, their name, and creation date. Your database would use a schema to describe this and reject any data that doesn’t fit into its requirements. By drawing hard lines between where data fits or doesn’t fit into a table, you know exactly what you’re getting with a schema database—data is consistent, relationships are clear cut, and there are no surprises. This can help improve data quality.

However, schema-based databases only work if your data is heavily formatted. Since strict guidelines are needed for data to fit into the table structure, schema-based databases cannot function without these guidelines.

However, schema-based databases only work if your data is heavily formatted. Since strict guidelines are needed for data to fit into the table structure, schema-based databases cannot function without these guidelines. Not only is this a very rigid way to work, but it means anything that is undefined must be stored outside your relational database or left behind altogether.

Schemaless or schema-free databases eliminate this pain point entirely. With a schemaless database, tech teams can enter data in whatever manner is most beneficial and efficient for the enterprise. In schema-free databases, all data is stored in JSON-style documents that can have different fields with different data types in each one. Every document has a partial schema used to make data retrieval faster, but that’s it. Any formal schema is applied deep within the code of your application, leaving the raw data untouched. This promotes flexibility and innovation.

A schemaless database:

  • Doesn’t make you conform to a rigid schema

  • Doesn’t enforce data type limitations

  • Doesn’t require any modeling

  • Can store structured AND unstructured data

  • Can be easily changed based on evolving needs

The advantages of going schema-free

At first, the idea that “less structure is better for managing large datasets” might seem frightening. But there are numerous benefits to using a schema-free database in a large enterprise. Take two of the most time-consuming aspects of database management as an example—database normalization and data extraction.

Database normalization

Normalizing your data so it fits into a relational database can take months, and you have to hire specialized database administrators to do it. Once every piece of data is in its proper table, it has to stay there for essentially its entire life. Any change to the relational database can cause anomalies and ruin the normalization your team took so much time to set up.

Schema-free databases eliminate database normalization almost entirely. This is because schemaless databases can accept any data type out there. Also, schema-free databases don’t make any significant changes to your data, which ensures every detail is always available and none are deleted or shortened to match a strict schema.

Data extraction

With a relational database, it’s tricky to pull data from external sources and put it into the staging area. First, the source and target both must understand the structure of the data in the relational world, and you also must have a solid understanding of the database’s table, column, and field layout. Second, there’s no way to extract and load data into the database without doing it in a batch stream, which means thousands of code lines and hours of work. Third, there’s not a lot of room for error as even the slightest misconfiguration could cause a disaster.

With a schema-free database, there’s no drawn-out transformation and data-cleansing process. Since there are no schemas to adhere to, a schemaless database model is incredibly flexible and can adapt to all types of data.

Other benefits of using a schema-free database include:

  • Increased scalability: Schema-free databases allow you to use whichever data model is the best fit for the job. You can query, report, and model information however you like, so your database can easily grow with you.

  • Increased flexibility over data types: Since you can store any data type in a schemaless database, you don’t have to be afraid of Big Data

  • Support for real-time analytics: Schemaless databases are better at processing real-time data than schema databases. This is a prime advantage for enterprises that use machine learning or artificial intelligence.

Schema-Free With MongoDB

Schemaless databases are the best choice for large enterprises looking to increase their scalability and flexibility, and they're also the top option for enterprises building with no-code. By letting you define your own data views, a schema-free database enables your non-technical staff to extract information quickly and easily. This saves your team time and money!

Unqork’s powerful no-code platform is supported through our partnership with the MongoDB Atlas database service, which is designed to optimize database design and management. MongoDB’s document model and cloud-agnostic approach let your software grow and evolve alongside your business developments. This enables you to create custom applications and continuously improve them on a never-ending scale.

Watch how easy it is to create a data workflow within Unqork’s schemaless database.

MongoDB also allows you to run your database on multiple clouds simultaneously, which can free you from detrimental cloud-vendor lock-in. Plus, you can trust that the data stored in your databases is secure. MongoDB is also designed with complete security features including data encryption in-transit and at-rest, high availability and reliability, and independently-audited compliance standards for data security.

With no-code, you can expedite builds of high-quality, customized software without complicated code lines or high development costs. By adding a schema-free database to that, you can streamline database management processes, increase flexibility, and help your enterprise web application reach new heights. 

To experience Unqork’s potential yourself, schedule a personalized demonstration with one of our in-house experts. Also, sign up for the Unqork newsletter for more no-code discoveries.