“Is Supabase Better Than MongoDB? This is a question that many developers and businesses find themselves asking as they navigate the myriad of database options available today. With the rise of web and mobile apps, choosing the right database to power your application is more important than ever. Two of the most popular open-source options are Supabase and MongoDB. But how do you know which one is the better choice for your needs?
In this comprehensive guide, we’ll compare Supabase vs MongoDB across critical factors like features, performance, scalability, querying, and more. By the end, you’ll have the knowledge to determine which database is the superior pick for your next project.
Overview of Supabase and MongoDB
Let’s start with a quick rundown of what each platform offers:
Supabase – An open-source alternative to Firebase that combines PostgreSQL as the database along with authentication, storage, and more tools to build full-stack apps faster.
MongoDB – A popular document-oriented NoSQL database known for flexibility, scalability, and high performance. MongoDB stores data in flexible JSON-like documents rather than tables and rows.
Both options provide databases that are scalable, secure, and easy to integrate with modern apps. However, they take different approaches based on their underlying architecture.
Supabase follows a relational structure with PostgreSQL under the hood. MongoDB is non-relational and document-based.
This core difference affects factors like data modeling, querying, and optimal use cases. We’ll explore those distinctions more throughout this guide.
Exploring the Debate: Is Supabase Better Than MongoDB?
Let’s start with a high-level feature comparison between Supabase and MongoDB:
|Mongo Query Language
|Full Text Search
As you can see, both options check the box for critical features like open source, scalability, replication, search, and mobile support.
But there are also key differences that stem from Supabase using a relational model while MongoDB is document-based.
Supabase has native support for multi-row transactions, a strict database schema, and advanced analytics. MongoDB offers greater flexibility without needing to define schemas upfront, auto-sharding for scaling, and a document model optimized for certain data structures.
Digging deeper, Supabase uses Postgres for transactional consistency, foreign keys, and complex querying. MongoDB is designed for high flexibility and throughput via documents.
Neither choice is inherently “better” here. It comes down to matching the strengths to your specific use case, which we’ll explore next.
Comparing Performance and Scalability
For apps that need to support heavy traffic and data loads, performance and scalability are critical factors in choosing a database.
Both Supabase and MongoDB provide excellent scalability, but they scale in different ways based on their architecture:
- Supabase leverages PostgreSQL native replication and sharding capabilities to scale horizontally. Adding read replicas helps manage heavy read traffic while sharding distributes writes across nodes.
- MongoDB scales via auto-sharding which automatically partitions and distributes data across clusters. MongoDB also provides horizontal scalability by adding more nodes.
In benchmarks, MongoDB often comes out ahead in terms of raw throughput and faster response times for simple queries on large datasets. The document model lends itself well to scalability and performance.
However, Postgres has advantages with more complex relational data models that require joins, transactions, and complex querying. For workloads involving a lot of inter-related data, Supabase can perform better.
So MongoDB may be preferable if you need blazing-fast performance on large simple data or datasets. But don’t rule out Postgres and Supabase for complex use cases that require robust relational capabilities.
Querying Differences Between Supabase and MongoDB
The data models behind Supabase (relational) and MongoDB (document-oriented) also affect their querying capabilities:
- Supabase uses PostgreSQL’s powerful SQL commands for querying. SQL allows you to join data across tables, include subqueries, create complex calculated fields, use aggregations, and much more.
- MongoDB uses a declarative JSON-based language for querying called the MongoDB Query Language (MQL). It allows you to query documents and embedded arrays and perform complex aggregations.
Which one you find easier comes down to whether you prefer SQL or JSON-style queries. Both enable ad-hoc queries to retrieve and analyze your data.
In terms of power, PostgreSQL has far more extensive querying capabilities given its status as an enterprise-grade RDBMS. But MongoDB extends JSON with helpful constructs like sub-documents and arrays for nested data and provides easy aggregation pipelines.
For most use cases, Supabase’s Postgres options provide greater querying flexibility. But MongoDB querying also shines for non-relational data models.
Supabase vs MongoDB for Multi-Tenant Apps
Modern SaaS applications often need to handle multi-tenancy – serving multiple customer groups from the same shared backend.
Both databases can support multi-tenant architectures in different ways:
- Supabase – Postgres schemas provide native support for multi-tenancy in Supabase. You can store data for different clients or organizations in separate schemas within the same database. Row-level security helps isolate data access.
- MongoDB – Multi-tenancy is enabled by creating collections and indexes for each client or tenant. MongoDB’s document model provides flexibility in managing access controls.
So in both databases, you can still maintain logical separation of data between tenants while running a shared application instance.
Postgres schemas give Supabase a bit more built-in separation. But MongoDB’s flexibility also allows multi-tenant designs tailored to app requirements.
If you need rigorous data isolation, Supabase may be preferable. MongoDB offers great flexibility for multi-tenant models.
Ease of Use for Developers
Developer experience is also crucial in choosing a database platform. Both Supabase and MongoDB aim to provide great APIs, drivers, and integration options.
A few highlights:
- Supabase uses PostgREST for a RESTful API with full CRUD endpoints generated automatically. Client libraries like PostgREST make integration intuitive.
- MongoDB has robust official drivers for languages like Node, Python, Java, and more. MongoDB also fits naturally with JSON-centric workflows.
- Docs & Support – both provide excellent documentation and community support resources for developers.
For many use cases, it comes down to using the right tool for your backend data model. Both databases aim to provide great usability.
Data Integrity and Durability
When choosing a database, ensuring durability and data consistency is essential. Losing data or ending up with incorrect data due to multi-user editing can break applications.
- Supabase uses PostgreSQL, which has robust ACID-compliant transactions. This prevents dirty reads or writes and guarantees consistency across rows and tables.
- MongoDB has more limited transaction support. However, MongoDB does provide atomic single-document operations.
PostgreSQL powering Supabase adds greater assurances for data validity across complex relational data. But MongoDB does provide transaction functionality for many situations via multi-document transactions.
If maintaining referential integrity across large, relational datasets is critical – Supabase has the edge. MongoDB offers sufficient transaction capabilities for many use cases but falls short of full ACID compliance.
What is Supabase Best Suited For?
Given the above comparisons, below are examples of use cases where Supabase shines:
- Relational data models with foreign key constraints
- Applications requiring complex SQL querying
- Analytics dashboards and reporting
- Apps needing multi-row transactions
- Legacy systems that relied on SQL databases
- Use cases where Postgres excels like geospatial data
The Postgres foundation makes Supabase a great choice where you need an open-source relational database with enterprise capabilities. Developers familiar with SQL appreciate Supabase’s intuitive querying.
What is MongoDB Best Suited For?
Based on its document-oriented approach, MongoDB is an excellent choice for:
- Applications with JSON-like or non-relational data
- Content management and blogging platforms
- High-throughput apps like real-time analytics
- Rapid prototyping and iterations where flexibility helps
- Complex nested data structures and hierarchies
- Don’t require complex relational data constraints
Example MongoDB Use Cases
Here are some examples of popular apps leveraging MongoDB’s strengths:
- YouTube uses MongoDB to store metadata and analytics on videos
- Buzzfeed relies on MongoDB to manage its high volume of content
- IKEA built its catalog app with MongoDB to store product data
- Coinbase uses MongoDB to manage blockchain transaction data
Key Takeaways: Supabase vs MongoDB
To summarize this in-depth comparison guide, here are the key takeaways:
- Supabase combines PostgresSQL with real-time functionality as an open-source Firebase alternative. Offers relational model with SQL querying.
- MongoDB provides a popular document database with support for nested JSON data. Great for flexible schemas and high scalability.
- For complex relational data models, strong analytics, and multi-row transactions – Supabase has advantages.
- For hierarchical data, simpler querying, flexible schemas, and high throughput – MongoDB is likely the better choice.
- Both offer excellent scalability, secondary indexes, mobile clients, and an open source ecosystem.
- Developer experience is excellent on both databases with available drivers, APIs, and documentation.
There is no universal “better” choice between the two databases. Evaluate their relative strengths against your application’s specific needs to determine the ideal fit.
Many modern apps may even leverage both relational and non-relational databases for different purposes. You can use Supabase and MongoDB together in a polyglot persistence architecture.
The most important step is to fully consider your requirements around data models, querying needs, scalability demands, and transactions to pick the optimal database.
Frequently Asked Questions
Is MongoDB better for large datasets?
In general, yes – MongoDB’s document model and auto-sharding capabilities make it well-suited for large or unbounded datasets. But Postgres can also handle sizable data via Supabase if needed.
Can Supabase handle user authentication and storage?
Yes! Supabase provides baked-in auth along with storage options. This makes it an end-to-end development platform.
What programming languages does MongoDB support?
MongoDB offers official drivers for Python, Node.js, Java, C#, Go, and many other languages. It fits nicely into modern tech stacks.
Is MongoDB entirely schemaless?
MongoDB is considered schemaless since documents in a collection can have different fields and structures. But indexes and validation rules allow enforcing schemas where needed.
Does Supabase offer a free tier?
Yes, Supabase has a generous free tier for testing and prototyping. Additional resources can be purchased based on usage needs.
Can GraphQL be used with MongoDB?
Not natively, but there are GraphQL middleware options like MongoDB’s Stitch to add a GraphQL API layer to MongoDB.
How do Supabase and MongoDB handle real-time data?
Supabase uses Postgres listeners for realtime updates. MongoDB has changed streams to subscribe to data changes. Both provide realtime capabilities.
Determining whether Supabase or MongoDB is “better” depends on your application’s specific requirements and the kinds of data you need to store.
As a relational SQL database, Supabase based on Postgres offers great support for complex querying, multi-row transactions, and traditional data models.
MongoDB’s document schemas provide higher performance for certain access patterns and greater flexibility.
Hopefully, this comprehensive guide provided you with the key factors to consider between these two popular databases. Evaluating your own needs around scalability, querying abilities, data models, and ease of use will point you to the right choice.
In some cases, both PostgreSQL and MongoDB can play important roles in a modern application architecture. Many teams use Postgres for relational workflows and MongoDB for high-performance media storage or analytics, for example.
The open-source ecosystems around both Supabase and MongoDB ensure they will continue to evolve and improve over time. Keep up to date with new features and releases to see how they can help your next project.