Supabase vs DynamoDB: Which Database Should You Choose?

The database you pick matters for how your queries run, how the system handles load, and how much work goes into keeping it running. 

Supabase uses PostgreSQL, so you get relational tables and real-time updates. DynamoDB is AWS’s managed NoSQL database, built for high scale and fast responses.

This guide covers how they differ in performance, cost, and operations, so you can decide which one fits your project.

What is Supabase?

Supabase builds on PostgreSQL to provide a backend-as-a-service platform. You get a managed PostgreSQL database with automatic REST and GraphQL APIs generated from your schema. It includes built-in authentication, file storage, and real-time subscriptions via WebSockets. Row-level security policies let you enforce access control directly in the database.

The codebase is open source under Apache 2.0, so you can self-host the entire stack or use Supabase’s managed hosting. It’s a good fit for startups building MVPs, internal tools that need SQL flexibility, or teams looking for Firebase-like features while staying in the PostgreSQL ecosystem.

What is DynamoDB?

DynamoDB is AWS’s managed NoSQL database. It stores data as key-value pairs or JSON documents and handles provisioning, replication, and scaling automatically. It uses a serverless model, so you pay for actual throughput and storage instead of running dedicated database servers.

The service runs across multiple availability zones, giving single-digit millisecond read latency and built-in redundancy. Global tables let you replicate data across regions with multi-master writes. DynamoDB also integrates with Lambda, API Gateway, and other AWS services through IAM. It’s well-suited for applications that need predictable performance at scale, especially if you’re already on AWS.

Data Models & Query Languages

Supabase: PostgreSQL, relational + real-time

Supabase uses standard PostgreSQL, so you work with tables, foreign keys, joins, and indexes. Relationships are enforced with foreign key constraints, matching how many developers structure data.

SQL provides flexibility for joins, aggregations, filters, and window functions. Triggers and stored procedures let you handle logic at the database level. PostgREST automatically turns tables into REST endpoints, so you can expose your data without extra backend code.

DynamoDB: NoSQL key-value/document model

DynamoDB stores items in tables with a required partition key, optionally using a sort key. Data is often denormalized, and some information may be duplicated to avoid joins.

Secondary indexes let you query on other attributes. Local secondary indexes share the partition key, while global secondary indexes allow different keys. Each index consumes extra storage and write capacity, so careful planning is needed.

How their query capabilities differ

SQL in Supabase allows ad-hoc queries across tables, with filters and aggregations, without predefining access patterns.

DynamoDB’s Query operation retrieves items from a partition, while Scan reads the whole table and can be slow at scale. Access patterns outside your keys often require extra tables, making upfront data modeling more important.

Scalability, Performance & Infrastructure

Supabase's architecture and performance benchmarks

Supabase runs PostgreSQL on dedicated instances. Free tiers use shared resources, while paid plans provide dedicated CPU and RAM. Performance scales with instance size, and reads generally perform well with proper indexing. 

Writes need more tuning, and connection pooling through PgBouncer helps manage concurrency, typically up to 500-1000 simultaneous connections. Higher loads require larger instances or read replicas.

Real-time updates use PostgreSQL’s logical replication and push changes via WebSockets. This works for dashboards or collaborative features but adds some load to the database.

DynamoDB's serverless infrastructure and scaling model

DynamoDB partitions data across storage nodes. Each partition handles up to 3000 read capacity units or 1000 write units per second. As the table grows, DynamoDB automatically adds partitions and redistributes data.

You can configure capacity in two ways. Provisioned capacity gives predictable performance but requires adjusting units as traffic changes. On-demand capacity scales automatically with traffic spikes, avoiding throttling but costing slightly more per request.

Single-item reads take single-digit milliseconds. Queries within a partition maintain similar latency. Global tables replicate data across regions with typical replication lag under one second. This setup supports high request volumes when access patterns align with partition key distribution.

When each approach makes sense

Supabase fits applications where relationships and flexible queries are important. Internal tools, dashboards, or admin panels that filter and sort data in multiple ways benefit from SQL flexibility. Small to medium workloads - up to a few hundred requests per second - run well with proper indexing and caching.

DynamoDB is better suited for high-scale applications with predictable access patterns. IoT systems, gaming leaderboards, or ecommerce catalogs can handle millions of users globally with low-latency responses. Its serverless model also adapts to variable traffic without requiring manual capacity adjustments.

Cost, Pricing & Operational Considerations

Supabase:

• Free tier ($0/month): 500 MB database, 1 GB file storage, 50,000 MAUs, shared CPU/RAM, 5 GB egress, community support. Projects pause after 1 week of inactivity.

• Pro plan ($25/month): 8 GB database, 100 GB storage, 100,000 MAUs (extra $0.00325 per MAU), 250 GB egress/cached egress, daily backups, 7-day log retention, email support.

• Compute: Starts at $10/month in credits. Instances range from Micro (1 GB RAM, 2-core) to 16XL (256 GB RAM, 64-core), scaling at any time.

• Self-hosting: Removes licensing fees but adds operational overhead - manage PostgreSQL instances, replication, backups, and monitoring.

• Hidden costs: Features like real-time subscriptions or auto-generated APIs require custom work if migrating away from Supabase.

DynamoDB:

• On-demand: Pay per request, automatic scaling. Example: 10M reads + 2M writes + 50 GB storage ≈ $20/month. Good for unpredictable traffic.

• Provisioned: Specify read/write units. Same 10M reads/writes could cost $10–15/month if traffic is steady.

• Extras: DAX caching (~$0.12/hour), global tables, backups ($0.20/GB).

• Operational notes: Minimal management, but upfront planning for keys and access patterns is critical. Poor design can cause throttling and high costs. Migration is complex due to AWS-specific patterns.

Operational considerations:

Supabase: You manage pooling, performance, query tuning, and storage planning. Standard PostgreSQL tools help migrations, though some features are Supabase-specific.

DynamoDB: Low operational overhead, but requires careful design. Scaling features add costs, and vendor lock-in is stronger.

Ecosystem, Features & Developer Experience

Supabase offers a web dashboard and a spreadsheet-like table editor. Client libraries generate typed APIs. Authentication supports OAuth, magic links, and phone sign-in, with Row-Level Security controlling access. Storage integrates with auth, and real-time subscriptions let clients watch tables, rows, or filtered queries - useful for chat apps, dashboards, or collaboration—though frequent updates need planning.

DynamoDB integrates with AWS via IAM. Lambda can read/write tables, and Streams enable event-driven workflows. API Gateway can proxy requests, but logic usually runs in Lambda. Partition keys, sort keys, and secondary indexes need careful planning. DynamoDB lacks built-in auth, file storage, or GraphQL; you combine Cognito, S3, and AppSync, which adds integration and monitoring work.

So, in short: Supabase provides a ready-to-use backend with auth, storage, and real-time updates. DynamoDB is modular and scalable but requires more upfront planning and integration.

Which One Should You Use When?

Scenario	Supabase	DynamoDB
MVPs / Startups	Fast setup, APIs, auth, real-time	AWS-native, needs planning
Reporting / Queries	Flexible SQL queries	Limited, extra tools needed
High-scale / Global	Medium workloads	Scales automatically, multi-region
Hybrid / Migration	Can pair with DynamoDB	Migration requires effort

Supabase works best for MVPs, internal tools, or applications with evolving schemas and complex queries. 

DynamoDB is best for high-scale, predictable workloads, and AWS-native serverless architectures.

Migration, Limitations & Future Considerations

Supabase limitations:

PostgreSQL scales vertically well, but CPU, memory, and connection limits eventually appear. Read replicas help reads but not writes. Horizontal scaling requires sharding, which Supabase’s managed service doesn’t provide. 

Connection pooling helps, though serverless functions with many short-lived connections can hit limits.

DynamoDB limitations:

Single-table design works for reads but can make schemas less intuitive. Adding access patterns often requires new indexes, increasing write costs. Denormalization adds storage needs and consistency work.

Default eventually-consistent reads may be stale; strongly-consistent reads cost more and don’t work across regions.

What to consider for growth and long-term strategy?

Teams with SQL experience can continue with Supabase longer, since skills transfer to other databases. DynamoDB’s patterns are AWS-specific. Costs scale differently: Supabase grows with compute and replicas, DynamoDB with per-request usage. 

Operationally, PostgreSQL needs some database administration at scale, while DynamoDB shifts complexity to designing data models. Your team’s experience and expected traffic should guide the choice.

Getting Started

If your app’s data and requirements are still evolving, Supabase makes it easier to iterate. If you’re running predictable, high-scale workloads on AWS, DynamoDB handles that efficiently.

Choose based on your team’s skills, expected traffic, and the infrastructure you already have in place.

You can also connect to our experts for help with database design, migrations, and integrating Supabase or DynamoDB into your applications.

Frequently Asked Questions

How do I migrate from DynamoDB to Supabase?

Export DynamoDB data as JSON using the AWS SDK or Data Pipeline. Map items to a relational schema, flatten nested attributes, and create tables in Supabase. Use scripts or Supabase client libraries to insert data, handling type conversions and constraints. Update application code to replace DynamoDB calls with SQL queries or Supabase client methods, adjusting key lookups and scans accordingly.

How do transactions work in Supabase vs DynamoDB?

Supabase uses PostgreSQL’s ACID transactions, supporting multiple tables and complex operations. DynamoDB offers transactions via TransactWriteItems and TransactGetItems for up to 100 items in a single region. Supabase provides more flexibility for complex logic; DynamoDB is suitable for coordinated updates but requires careful planning.

Can I use GraphQL with DynamoDB like Supabase?

Supabase generates GraphQL APIs automatically from the database schema. DynamoDB requires AWS AppSync or a custom GraphQL server with resolvers, which adds configuration and maintenance overhead.

Can I self-host DynamoDB like Supabase?

No. DynamoDB is AWS-only. DynamoDB Local exists for development but isn’t production-ready. Supabase is fully self-hostable, giving complete control but requiring infrastructure management. Alternatives like ScyllaDB or Cassandra can mimic DynamoDB, but migration and API differences apply.

What’s the largest deployment of each platform?

DynamoDB powers Amazon.com, handling millions of requests per second, and is used by Lyft, Samsung, and Capital One. Supabase, launched in 2020, powers companies like Replicate and Mobbin. PostgreSQL itself scales to the level of Uber, Netflix, and Instagram with proper architecture. Both require careful design to achieve high performance.