Overview
Free database options split into five distinct jobs. Relational Databases handle structured, joined data for a typical application backend. NoSQL Databases trade joins for flexible documents or key-value pairs that scale horizontally. Vector Databases store embeddings and run similarity search for AI retrieval. Analytics Databases are built for large scans and aggregation rather than single-row lookups. Serverless Databases cut across several of those data models, but share one property: they bill for actual usage and scale down to nothing when idle. A free cloud database in any of these groups is only worth comparing once you know which job you actually need done.
What to look for in a free cloud database
A useful free online database gives you enough room to build something real, not a demo you outgrow in a week. For a relational service, that means enough storage and connection headroom to run an actual schema under real traffic, not just a sample table. For a document or key-value store, request volume and item count matter more than raw storage. A free cloud relational database also has to behave like the paid tier above it, with the same replication model and the same backup story, so what you build during the free period keeps working after you outgrow it.
The catch with most free database tiers is rarely the headline limit itself, it's what happens around it. Some services pause an idle project after a stretch of inactivity, which is fine for a side project and disruptive for anything with real users. Others meter by request or compute time rather than by storage, so one slow query or a missing index can burn through a month's allowance faster than the pricing page suggests. Vector databases in particular often cap the number of indexes or collections before they cap storage, which starts to matter once you're running more than one embedding model.
Gotchas to watch for
Match the data model to the job before comparing free tiers against each other. Reach for a relational or serverless database when you need joins and transactions, not just key lookups. Pick a NoSQL store when the data is naturally a document or a key-value pair and you'd rather skip a migration for every shape change. Choose a vector database once you actually have embeddings to search, and an analytics database once a single application database can't answer your reporting queries fast enough.
10 free databases tiers compared
| Product | Type | Free tier includes | Est. value | Card required |
|---|---|---|---|---|
| Neon Serverless PostgresFTV 60 | Free tier | Provides 0.5 GB storage per project. | Not stated | No |
| SupabaseFTV 56 | Free tier | 500 MB database size per project. | $25 / month | Not stated |
| Cloudflare D1FTV 46 | Free tier | Up to 5 GB total storage included. | $5.00 / month | Not stated |
| CockroachDBFTV 51 | Free tier | 50 million request units and 10 GiB storage free per month. | $2.00 / month | No |
| TursoFTV 56 | Free tier | Includes 5 GB total storage. | $4.99 / month | No |
| MongoDBFTV 44 | Free tier | 512 MB of storage included. | $8.00 / month | Not stated |
| Azure Cosmos DBFTV 52 | Free tier | 25 GB storage free each month for the lifetime of one Azure Cosmos DB account per Azure… | Not stated | Not stated |
| Amazon DynamoDBFTV 40 | Free tier | 25 GB of data storage per month on DynamoDB Standard tables. | $8.50 / month | Not stated |
| ConvexFTV 50 | Free tier | 0.5 GB database storage total. | $8.50 / month | Not stated |
| QdrantFTV 46 | Free tier | 0.5 vCPU, 1 GB RAM, and 4 GB disk storage. | $8.00 / month | Not stated |
Best free databases picks by use case
Best for: You need a relational database that keeps working through a regional outage
CockroachDB replicates data across regions automatically and speaks the Postgres wire protocol, so an app built against Postgres drivers can point at it directly. It fits teams that want distributed resilience without redesigning their data layer.
Best for: You want a serverless Postgres database that scales compute to zero between requests
Neon separates storage from compute, so an idle branch costs nothing to keep around and a fresh one can be created for every pull request. That branching model suits teams that want a full copy of production data for every feature branch.
Best for: You need a flexible document store that most backend frameworks already support
MongoDB's document model absorbs nested, evolving data without a migration for every schema change, and its driver ecosystem covers nearly every backend language. The free Atlas cluster is meant for learning and small projects rather than production traffic.
Best for: You're adding semantic search or retrieval-augmented generation to an app
Qdrant runs as a single-node cluster you query the same way you would in production, so a prototype's retrieval logic carries over directly when you move to a paid deployment. It also supports hybrid dense-and-sparse search, which many vector-only stores skip.
Best for: You need to run analytical SQL over a growing dataset without standing up a warehouse
MotherDuck runs DuckDB in the cloud, so the fast, columnar engine you'd otherwise run locally scales against shared storage without a change in query engine. It suits a small team that wants warehouse-style analytics without warehouse-style operations.
Frequently asked questions
What's the real difference between a free cloud database and a free trial?
A free cloud database tier keeps working indefinitely as long as you stay under its usage limits. A free trial gives full access to a paid plan for a fixed window and then asks for payment or a downgrade, so check which one you're looking at before you build against it.
Which free tier fits a typical web app's database?
A relational free tier is the usual starting point for an app with users, orders, or anything that needs joins across tables. Reach for a NoSQL free tier instead when the data is naturally document-shaped and you don't need multi-table transactions.
Is a serverless database a good fit for a side project?
Yes, often a better one than an always-on instance, because a serverless database scales down to nothing between visits instead of billing for idle compute. The tradeoff is a cold start on the first request after a quiet stretch.
What should I check before picking a free vector database?
Look at how many indexes or collections the free tier allows, not just total storage, since a project usually needs a separate index per embedding model or use case. Also check whether hybrid keyword-plus-vector search is included or sold as an add-on.
Do free database tiers require a credit card?
It varies by vendor and sometimes by signup method, so check the specific listing before you sign up. Card requirements change more often than headline storage or request limits do.
Can one database cover relational, document, and vector workloads at once?
A few products advertise multi-model support, but a database tuned for one workload usually outperforms a generalist at that same workload. If you need more than one data model, running a dedicated free tier for each is usually simpler until performance actually forces a consolidation.
