How Much Are Free Database Credits Worth?
Free database credits for startups run from $300 at the low end to $100,000 per program at the top, and because each vendor invoices you separately, the grants add up rather than overlap.
The seven named programs below clear $256,000 combined, before counting the database capacity that sits inside a general cloud grant from AWS, Google Cloud or Azure.
AI Perks tracks the current terms across the category alongside $7.7M in credits from 194 companies.
| Provider | Free credits | What the credits buy |
|---|---|---|
| Neon | Up to $100,000 | Serverless Postgres with database branching |
| Aiven | Up to $100,000 | Managed Postgres, MySQL, Kafka, ClickHouse, OpenSearch, Valkey |
| MongoDB Atlas | Up to $25,000 | Document database with full text and vector search |
| Neo4j AuraDB | Up to $16,000 | Managed graph database |
| Redis Cloud | Up to $10,000 | In-memory cache, sessions, queues, vector search |
| Elastic Cloud | Up to $5,000 | Search, log analytics and vector retrieval |
| Supabase | $300 | Postgres plus auth, storage and edge functions |
| AWS, Google Cloud, Azure | Six figures at the top tiers | Managed databases billed inside the cloud account |
Those figures are not directly comparable. A $16,000 grant with a vendor whose list prices are high can buy fewer months of runway than a $10,000 grant somewhere cheaper, so read the column as time bought, not as value received.
What Managed Database Credits Actually Cover
Credits pay for the managed service wrapped around the database, not for the database engine itself. Postgres, MySQL, Redis, OpenSearch and Valkey are all open source and free to run yourself.
What you are actually buying is the operational surface around it: uptime, failover, backups, patching and support. That is the bill a credit offsets.
Framed properly, a large database grant buys a startup the year in which it does not need an infrastructure hire. That is usually worth more than the dollar figure printed on the program page.
Five line items sit inside almost every managed database invoice:
Provisioned compute. The instance or plan size you selected, billed whether or not it is busy.
Storage and IOPS. Data at rest, plus the throughput tier on top of it.
High availability. A standby replica roughly doubles the compute line before serving a single extra query.
Backups, egress and support. Retained snapshots, data transfer out, and the support tier production requires.
How Database Costs Behave at Scale
Database spend is a standing monthly floor set by provisioned capacity, not a usage curve that follows traffic. A quiet week costs exactly what a busy week costs.
This is the sharpest difference from model API billing, where traffic and cost move together. It changes how credits should be timed: a database grant starts draining the day you provision, whether or not anyone is using the product.
The bill also moves as a step function rather than a slope. Costs sit flat while you grow into an instance size, then jump when you cross it. Teams are routinely surprised by a doubling in month seven that reflects one resize, not a doubling of usage.
Serverless Postgres partly breaks this pattern. Neon and the serverless tiers from the major clouds scale compute toward zero when idle, which is what made branch-per-pull-request environments affordable. The catch is that idle rarely means idle: a connection pooler holding open connections, a cron job, or a health check will keep an instance warm and quietly reinstate the floor.
Three multipliers do most of the damage at scale: replication factor, environment count and retention window. Staging, preview and analytics replicas are each a real instance with a real bill, and most cost overruns are a copy problem rather than a scale problem. AI Perks covers which providers currently fund those non-production environments through their startup programs.
How to Choose Between Postgres, MongoDB, Redis and Elastic
Start with Postgres unless you have a specific reason not to. Most of the other stores in the table are additions to a Postgres-shaped architecture, not replacements for it.
A short decision guide:
Default choice: managed Postgres. Neon, Supabase, Aiven and the cloud providers all offer it. Relational tables, JSONB for semi-structured data and pgvector for embeddings cover an enormous share of startup workloads in one system with one backup story.
Document data and fast-moving schemas: MongoDB Atlas. Worth it when your objects are genuinely nested and your schema changes weekly. Atlas also carries full text and vector search on the same cluster, which removes a second vendor.
Caching, sessions, rate limiting and queues: Redis. Almost never your primary store, almost always your second one. Because it bills on provisioned memory, its cost is predictable and its credits are easy to plan against.
Relationship-heavy queries: Neo4j. Fraud rings, identity resolution, supply chains and GraphRAG retrieval. The signal is recursive joins in SQL that get slower every quarter.
Log analytics and search at volume: Elastic Cloud. Full text search on your primary Postgres works well until it does not, and observability data is the fastest-growing dataset most startups own.
Streaming alongside transactions: Aiven. Its grant covers Postgres, Kafka and ClickHouse under one ceiling, which makes it the most efficient single application if you already run an event pipeline.
Most production stacks end up with two or three of these. Your credit strategy should mirror the stack you will actually run, not the one database you started with. AI Perks lists which of these have open programs right now.
What Database Credits Stack With, and What Order to Apply In
Database credits stack cleanly with cloud credits, model credits and observability credits, because those are four separate invoices. Apply to the vendor you already pay first, the large ceilings second, and short trials last.
First, the database you already run. Credits attach to a bill you are already paying, with no migration and no architectural commitment. This is the cheapest approval in the category.
Second, the large ceilings. Neon and Aiven sit at the top of the range. These are worth applying for even before you commit, because an approved grant is a legitimate input into an architecture decision that you would otherwise make on list prices alone.
Third, data infrastructure billed outside your cloud account. MongoDB Atlas, Redis Cloud and Elastic Cloud invoice you directly, which means their credits stack with AWS, Google Cloud or Azure startup credits instead of being consumed by the same bill.
Fourth, the cloud grants themselves. Managed database services are billed inside the cloud account, so a cloud credit is partly a database credit. This is the layer most founders underuse.
Last, small trials. A $300 credit is sized for a benchmark against your own data. Trigger it in the week you plan to run that benchmark, not months earlier.
Eligibility depends on stage and funding, and the requirements differ for every program in the table above. The current details for each are listed at getaiperks.com.
What Founders Get Wrong About Database Credits
The most expensive mistake is letting the size of a grant choose the database. Moving a production database is the hardest migration in the stack, and a large credit that pushes you onto a bad fit costs more in engineering time than it ever saves in hosting.
Four patterns worth avoiding:
Over-provisioning because it is not your money. Teams run three times the instance they need while credits last, then meet the real bill at list price. Size for what you intend to keep paying.
Ignoring what happens at zero. Credits end. Data has gravity, and by the time the grant runs out the cost of leaving is at its highest point. Model the post-credit bill before you commit.
Funding one database and forgetting the second. Almost every stack acquires a cache and a search index. Both are separate invoices with separate programs, and both are usually left unfunded.
Starting the clock on an empty database. Time-boxed credits granted before you have a workload spend most of their value on an idle instance.
Founders who fund the whole data layer rather than one vendor end up furthest ahead. AI Perks tracks $7.7M in credits across 194 companies so the database, the cache, the search index and the model calls can all be covered at the same time.
Frequently Asked Questions
Which database gives startups the most free credits?
Neon and Aiven sit at the top of the category at up to $100,000 each, followed by MongoDB Atlas at up to $25,000 and Neo4j at up to $16,000. Cloud provider grants reach six figures and include managed databases inside them. Current terms for each are tracked at getaiperks.com.
Can I stack database credits with AWS or Google Cloud credits?
Yes, provided the database vendor invoices you directly. MongoDB Atlas, Redis Cloud, Elastic Cloud, Neon and Aiven bill outside your cloud account, so their credits offset a bill that cloud credits never touch. Databases you run inside AWS or Azure are covered by the cloud grant instead, not on top of it.
Do I need a separate database for vector search?
Usually not at first. Postgres with pgvector, MongoDB Atlas and Redis all support vector search inside a database you already run, which avoids a second vendor and a second backup story. A dedicated vector engine earns its cost at larger scale or with heavy metadata filtering. See both categories at getaiperks.com.
What does a production database actually cost without credits?
A small single-instance database typically costs tens of dollars a month. Production with a standby replica, backups, a staging copy and a support tier commonly lands in the hundreds, and data-heavy teams reach four figures monthly. The multiplier is usually environment count and replication, not query volume.
Is serverless Postgres cheaper than a provisioned instance?
For bursty or intermittent workloads, usually yes, because compute scales toward zero when idle. For steady high-utilisation production traffic, a provisioned instance is often cheaper per hour. The break-even depends on your duty cycle and on whether connection poolers or cron jobs keep the instance permanently warm.
What happens when my database credits run out?
The full list-price bill arrives, usually at the point where migrating is hardest. Treat the credit as runway rather than as a discount: size instances for the bill you can afford afterwards, and apply to the next program before the current one expires. Programs are tracked at getaiperks.com.
Run the database. Let someone else pay for the instance.