A managed database removes some infrastructure work, but the application still needs a clear data model, recovery plan, and cost boundary. A service that looks inexpensive for an idle prototype may behave very differently with constant traffic, multiple environments, or a requirement to keep operating through a regional failure.
Supabase, Neon, PlanetScale, MongoDB Atlas, and Cockroach Continuum offer substantially different starting points. This comparison focuses on selecting the application’s hosted data store, using official information checked October 15, 2026. It does not claim benchmark results, hands-on migration testing, or verification of a provider’s availability promises.
Choose the database responsibility separately from surrounding tools. Our database client comparison addresses the desktop interface used to inspect data. Our application hosting guide covers running the application itself. A managed database needs its own decision about engine compatibility, topology, recovery, and consumption.
Compare the data and operating model
| Product | Best fit | Main strength | Meaningful tradeoff |
|---|---|---|---|
| Supabase | Postgres with connected backend services | Database and application backend context | Subscription, project compute, and usage combine |
| Neon | Elastic Postgres environments | Branching and compute that can scale down | Active time and retained history affect spend |
| PlanetScale | Several managed SQL deployment needs | Postgres and sharded engine choices | Topology changes both cost and operating assumptions |
| MongoDB Atlas | Document-oriented applications | Managed MongoDB with adjacent data services | Relational compatibility is a separate migration question |
| Cockroach Continuum | Distributed SQL requirements | Explicit availability and deployment editions | Provisioned resources and region choices matter |
Supabase
Supabase packages Postgres with backend services such as authentication, storage, and APIs. That is useful when a product team wants those services to share the application’s data context. The decision extends beyond buying a database connection: assess how identity, application access, and stored objects relate to the schema.
The advantage is a connected starting environment for a Postgres application. The limitation is assuming that the base plan price covers every project and workload. Model production, staging, previews, database compute, file storage, egress, and optional services separately. A second environment is an operating requirement even when it has little user traffic.
Pro starts at $25 per month. Paid plans include $10 monthly compute credits, sufficient for one Micro instance, while additional projects and larger compute add cost. Usage beyond included allowances is billed separately. The free plan has limited resources and pauses inactive projects, so it should not be treated as an equivalent production contract. Supabase fits teams that value a Postgres-centered backend and can manage the access model and combined usage bill.
Neon
Neon emphasizes elastic Postgres compute, branching, and separation between database activity and retained data. Its current offering also includes a growing backend suite. Branching is relevant for teams creating development or preview environments, but evaluate the lifecycle of those environments as carefully as their initial creation.
The strength is matching compute activity to changing workloads while keeping a familiar Postgres model. The tradeoff is that retained storage, change history, branches, snapshots, network transfer, and backend services can still contribute costs when the main workload is quiet. Test the application’s behavior when compute resumes and decide which environments should remain active.
Launch currently lists $0.106 per compute-unit hour and $0.35 per GB-month of database storage. Its displayed $15 monthly typical-spend example is a scenario, not a fixed subscription price or cap. Scale has different rates and entitlements. Free allowances are also bounded by project and resource limits. Neon suits teams with variable Postgres demand and a disciplined process for creating, protecting, and retiring development branches.
PlanetScale
PlanetScale’s current pricing distinguishes Vitess for MySQL-compatible sharding, Neki for sharded Postgres, and PlanetScale Postgres configurations. The product should therefore not be evaluated as one undifferentiated database plan. Start by selecting the engine and topology your application’s queries and transactions actually require.
The advantage is a range of managed SQL options, including different approaches to scale and availability. The limitation is that a low-cost single-node configuration and a multi-replica or sharded deployment solve different operating problems. Check extension and driver compatibility, transaction behavior, migration requirements, and the consequences of a node failure using the intended configuration.
The page lists PlanetScale Postgres single-node deployments from $5 per month and Metal configurations from $50 per month. Those entry figures do not price every highly available or sharded cluster. Compute, routers, shards, replicas, storage, backup storage, network usage, and add-ons can affect the total. Enterprise and own-cloud arrangements have further terms. PlanetScale fits teams able to choose a deliberate SQL topology and estimate resources for that choice rather than compare only starting prices.
MongoDB Atlas
MongoDB Atlas is the relevant option here when the application’s primary model is MongoDB’s document database. Its platform adds services such as search, vector search, and stream processing around managed clusters. Those can reduce some integration work, but they should be evaluated as additional workload and billing decisions.
The strength is operating MongoDB within a managed cloud environment. The limitation is assuming that a relational application’s schema and query behavior transfer without redesign. Demonstrate representative reads, updates, indexing, and reporting with the actual driver and application code. A familiar administrative interface does not resolve differences in data modeling or transactions.
Atlas lists a free shared tier, Flex from $0.011 per hour with a stated $30 monthly maximum for that tier, and Dedicated from $0.08 per hour. Region, configuration, storage, transfer, support, and added services determine the production bill. Do not apply the Flex cap to Dedicated or the entire Atlas platform. MongoDB Atlas suits teams intentionally using a document model and prepared to size cluster and adjacent services together.
Cockroach Continuum
Cockroach Continuum is Cockroach Labs’ current offering for new cloud organizations under the pricing introduced September 15, 2026. Its page distinguishes Standard on shared infrastructure from Mission Critical on dedicated infrastructure, with different availability and support scope. Existing customers may remain on earlier pricing unless they opt in.
The advantage is explicitly connecting the database deployment to a distributed SQL requirement. The limitation is treating that as a drop-in operational substitute for any Postgres service. Validate application compatibility, latency-sensitive transactions, region placement, and failure behavior against the intended topology. A high availability target requires a specific deployment and contract.
Billing includes provisioned vCPU time, storage, backups, transfer, and enabled add-ons, with rates varying by region and edition. Idle provisioned clusters still incur charges. The current page shows differing Standard rate examples between its headline and detailed matrix, so obtain a region-specific estimate rather than present one universal rate. A 30-day $400 trial credit is not a permanent free tier. Consider Continuum when distributed operation is a defined requirement with an owner and budget.
Evaluate a workload and its recovery boundary
Prepare a workload description before requesting prices: data size, expected growth, query patterns, connection count, busiest periods, and acceptable interruption. Separate production from development and preview environments. Include the storage and recovery history retained after an experiment or branch stops receiving queries.
Run a representative application evaluation instead of relying on generic benchmark rankings. Use a transaction that matters to the business, a reporting query, an index change, and a realistic burst of connections. Explain which part of the stack limits performance before increasing compute. Record configuration and cost assumptions so that the next estimate remains comparable.
Define recovery in concrete terms: what data must be recoverable, how old it can be, who initiates restoration, and where the restored database will run. Ask about retention, regional dependencies, backup charges, and export portability. An available backup feature is not evidence that your team has completed a recovery exercise.
- Confirm engine, driver, extension, and transaction compatibility.
- Price compute, topology, storage, history, transfer, and support.
- Inspect project and branch cleanup without losing required records.
- Define connection management, access roles, and deployment ownership.
- Document recovery objectives and a realistic exit path.
Shortlist Supabase for a connected Postgres backend, Neon for elastic Postgres environments, and PlanetScale for a deliberate managed SQL topology. Choose MongoDB Atlas when the document model fits the application, and assess Cockroach Continuum when distributed SQL requirements justify it. The strongest choice is the one whose workload, recovery, and monthly cost your team can explain.
Official sources
Checked October 15, 2026: Supabase pricing; Neon pricing; PlanetScale pricing; MongoDB Atlas pricing; Cockroach Continuum editions and pricing. Estimates require the intended cloud region and actual resource configuration.
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