9 Best Serverless Databases for Modern Applications in 2025

Dear reader, if you‘re looking to build a modern application with an unpredictable workload, this comprehensive guide on serverless databases is for you.

As a lead data architect with over 15 years of experience, I‘ve helped numerous companies transition to serverless architectures to improve scalability and reduce costs. In this guide, I‘ll share my research and insights to help you choose the best serverless database for your needs.

Why Serverless Databases Are the Future

Traditional databases require provisioning fixed servers upfront based on peak estimated capacity. This results in overprovisioning and high costs for variable workloads.

Serverless databases are designed to provide real-time data access and auto-scale compute resources based on actual usage per second. This "pay as you go" model is perfect for modern applications with unpredictable traffic.

According to Gartner, over 50% of databases will transition to serverless offerings by 2025. The key drivers are:

• Improved productivity – Developers spend less time managing infrastructure and more time building apps. Serverless DBs take care of provisioning, patching, scaling, high availability and more.

• Cost savings – With per-second billing, costs precisely align with usage patterns. No more overpaying for idle capacity. Azure Cosmos DB and AWS Aurora Serverless can reduce TCO by up to 68%.

• Faster innovation – Serverless allows iterating quickly and trying new ideas with minimal overhead. No need to manually scale databases or shard data as usage grows.

• Flexibility – Serverless databases can be configured as relational, document, graph, and key-value models to best fit each microservice. Many support cross-region replication and hybrid/multi-cloud deployments.

It‘s clear that serverless represents the future of databases in the cloud. Now let‘s explore the top serverless database options for modern apps.

Top 9 Serverless Databases for the Cloud

1. Fauna – Most Flexible Serverless Database

Fauna is my top recommendation for a flexible serverless database. Here‘s why:

• Supports key-value, document, relational and graph data models in a single database. Easily evolve schemas without migrations.

• Low latency and high throughput even at global scale with ACID transactions. Benchmarked at over 60k ops/sec on a single node.

• Fully managed with automatic scaling, replication, failover, and robust security.

• Integrates with popular languages like JavaScript, Python, Go, and Java. Rich query language via FQL, GraphQL and REST APIs.

• Portable architecture runs anywhere – public cloud, private cloud, on-premises or directly embedded inside applications.

Fauna started as a distributed NoSQL document store but expanded into a multi-model database capable of handling any use case. It‘s the only database I know that combines flexibility, performance, and cloud-native management as cleanly as Fauna.

Whether you need blazing fast key-value, complex document relationships, graph traversal or relational joins, Fauna has you covered. I‘m seeing many customers migrate from MongoDB, Neo4j, Redis and MySQL to simplify their stack with Fauna.

Pricing is based on document reads/writes and storage used. Fauna scales linearly with no painful sharding required. It‘s a fantastic choice if your application needs extreme flexibility.

2. Amazon Aurora Serverless – Best Managed Relational Database

If your app relies on a relational data model, Amazon Aurora Serverless is an excellent serverless choice. Here are the key advantages:

• Fully compatible with MySQL and PostgreSQL for easier migration from legacy RDBMS.

• Up to 5x better performance than MySQL and 3x than PostgreSQL according to AWS.

• Distributed storage architecture for high availability and fast scalability up to 64TB.

• Handles provisioning, OS patching, backups, replication, failure recovery, and more.

• Auto-scales compute capacity between 10 ACUs to 256 ACUs based on actual usage.

Amazon cites customers like Intuit and Wealthfront who use Aurora Serverless to cut database costs by up to 65%. It‘s a fantastic relational database option if your application is already optimized for MySQL or PostgreSQL.

The automated scaling and management are perfect for teams that want to focus on product innovation rather than database admin. Aurora Serverless is my standard recommendation for serverless relational workloads on AWS.

3. Azure Cosmos DB – Optimized for Global Applications

Azure Cosmos DB is Microsoft‘s premium database service for globally distributed applications. Here are the key highlights:

• Turnkey replication across any number of Azure regions with multi-homing APIs for local HA.

• Guaranteed single-digit millisecond latencies at 99th percentile backed by SLAs.

• Automatically scales storage and throughput elastically across regions.

• Choice of document, key-value, wide-column and graph data models.

• Functions as a MongoDB, Cassandra, Gremlin, and Table API endpoint.

Cosmos DB is trusted by many enterprises needing a fast, globally distributed database like Coca-Cola, Walgreens, and Renault-Nissan. Costs are optimized by scaling throughput directly based on application needs per region.

The guaranteed low latency and multi-model capabilities make Cosmos DB ideal for geographically dispersed applications. It‘s very competitively priced compared to other globally distributed databases.

4. PlanetScale – Fully Managed MySQL

PlanetScale brings MySQL into the serverless era. Key benefits:

• Fully compatible version of MySQL 8 powered by advanced Vitess clustering.

• Managed service on Kubernetes handles provisioning, scaling, patching, backups.

• Branching allows fast parallel development, testing and promotion to production.

• Auto-scaling and pay-per-use pricing to handle unpredictable workloads.

• Free developer tier and SLAs on uptime and performance.

If your team prefers working with traditional MySQL, PlanetScale is a great serverless choice. There‘s minimal code changes needed to migrate existing MySQL apps.

Under the hood, it uses battle-tested Vitess technology pioneered at YouTube to scale MySQL horizontally. PlanetScale automates these complexities leaving your team to focus on the application logic.

Pricing is competitive – up to 4x cheaper than Amazon RDS according to PlanetScale. Definitely give it a look if MySQL is your preferred relational database.

5. YugabyteDB Serverless – Redis-compatible Database

YugabyteDB Serverless provides a fully managed, cloud-native distributed SQL database. Here are the highlights:

• Built-in compatibility with Redis for easy migration from open source.

• Auto-scaling, self-healing, and auto backups handled by service.

• Distributed ACID compliance and strong consistency across regions.

• Query capability through PostgreSQL wire protocol and distributed SQL queries.

• Multi-region support available on Google Cloud Platform.

YugabyteDB Serverless allows teams to get the benefits of a distributed SQL database without operational overhead. Performance is excellent with ultra-low latencies and high throughput capacity.

Their "Redis-compatible but SQL-native" approach makes YugabyteDB Serverless very appealing for applications transitioning from open source Redis to a managed cloud service. Costs are very competitive with up to 4x savings compared to Memorystore for Redis according to Yugabyte.

6. Upstash – Serverless Alternative to Redis

If your application relies heavily on Redis for caching, queues, or ephemeral data storage, check out Upstash. Here‘s what you get:

• Fully Redis-compatible to leverage existing code and tooling.

• Auto-scaling to handle unpredictable workloads, including 0 usage.

• Sub-millisecond latencies for fast performance.

• Managed service on AWS, GCP and Azure handled by Upstash.

• Granular pay-per-use pricing for storage, memory and bandwidth.

Upstash provides Redis semantics without having to manage Redis infrastructure. Everything is abstracted as a service while your app directly interfaces with a Redis data store.

It‘s purpose-built for serverless applications that leverage functions and containers. Upstash auto-scales seamlessly as your functions scale up and down.

If your use case fits Redis well, I recommend Upstash over managing Redis yourself. It will save you effort while providing very fast performance.

7. Xata – Search and Analytics Focused

Xata is an intriguing new serverless database optimized for embedded search and analytics. Here are the key features:

• Allows complex relational data modeling while auto-indexing everything.

• SQL-like query language that performs aggregations and analytics server-side.

• Change feeds to react to data changes from frontend in realtime.

• Handles scaling, ACID transactions, security, redundancy under the hood.

• Currently limited to US region but global expansion is planned.

Xata is interesting because it provides functionality you‘d expect from a search index or data warehouse, but as an auto-scaled serverless database.

The ability to model relationships while leveraging embedded analytics and search makes Xata very versatile. It‘s a good fit if you want those capabilities without managing search services or a data warehouse.

Pricing is based on queries and storage volume. Performance is excellent according to customers, but currently limited to a US single region deployment. One to evaluate further as Xata expands to other regions and cloud platforms.

8. Datomix Cloud – Multi-Model Serverless Database

Datomix Cloud is an interesting new multi-model serverless database option. Here are the key capabilities:

• Provides distributed key-value, document, and relational APIs from one clustered data layer.

• Built on the high-performance Datomix framework used in financial services.

• Fully managed as a serverless service on AWS and Azure.

• Auto-scales resources to any volume with enterprise-grade security.

Datomix offers strong data consistency, high availability, and cross-region replication as managed services. You don‘t need to configure these complexities yourself.

It‘s essentially an "open source-compatible" platform similar to PlanetScale for MySQL. If you like the capabilities of Kafka, Cassandra, or Redis but want it fully managed, Datomix Cloud is worth evaluating.

Pricing is based on throughput units and storage consumption. Given that Datomix targets the financial sector, I‘d expect the SLAs and support to be very robust. An interesting new managed provider to watch.

9. CockroachDB Serverless – Distributed SQL Database

CockroachDB Serverless brings the power of CockroachDB‘s distributed SQL database to a serverless model. Highlights include:

• Builds on the open-source CockroachDB project used widely in banking and finance.

• Auto-scaled to any workload size and billed per second of usage.

• Multi-tenant capable for cost efficiency in larger organizations.

• Handles provisioning, tuning, monitoring, alerting, and upgrades.

• Available on AWS, Google Cloud and Azure. Supports multi-cloud deployments.

For teams already using open source CockroachDB, the serverless product simplifies operations significantly. You get proven distributed SQL capabilities without infrastructure headaches.

Cockroach Labs emphasizes support for spiky, bursty workloads that need to scale up and down quickly. Costs can be 60% lower than provisioning your own clusters.

Multi-tenancy support is notable – this allows departments or customer accounts to securely share the same database cluster resources.

If you need rock-solid distributed SQL and like CockroachDB‘s technical approach, their serverless database offering hits the sweet spot.

How to Choose: Key Criteria and Decision Drivers

With so many compelling options, how do you narrow down the ideal choice? Start by considering these key decision criteria:

Data Model Needed

• Relational for complex queries, joins, and transactions
• Document for flexibility with nested schemas
• Graph for highly connected data
• Key-Value for simplicity like caching

Fauna‘s flexibility to support multiple models in one distributed database is powerful. PlanetScale provides full MySQL capability as a service.

Performance Needs

• Throughput capacity for reads and writes
• Latency required for real-time use cases
• Scalability needs over time

Fauna benchmarks very high on throughput while CosmosDB offers single-digit millisecond latency guarantees.

Operational Requirements

• Fully managed or self-hosted options
• Global deployment needs or regional only
• Integrations with other services
• Security compliance needs

Azure CosmosDB leads for globally distributed applications. AWS Aurora Serverless fully manages DB operations.

Team Preferences

• Aligns with existing experience like PostgreSQL or Redis
• Fits internal skillsets and resources
• Easy to trial and onboard

PlanetScale provides a familiar MySQL environment while Upstash mimics Redis.

Budget Limitations

• Free tier for development testing
• Predictable spending based on usage
• Budget thresholds per month

Upstash, Xata and Fauna offer free tiers. Serverless models provide transparent, aligned spending.

By weighing these key criteria against organizational priorities, you can determine the best serverless database for your application needs.

I always advise customers to run small proofs of concept against 2-3 shortlisted options before committing fully. This allows your team to validate technical fit and pricing assumptions.

Key Takeaways and Advice

Here are my closing recommendations based on all the options covered:

• Start with your data – Model it appropriately to pick the right technology, then let the database handle scaling and distributed topologies.

• Focus on app innovation – Serverless databases eliminate time spent managing infrastructure. Spend this high-value time perfecting your product experience.

• Design for flexibility – Choose an adaptable solution able to accommodate unexpected use cases in the future as needs grow.

• Leverage managed services – The expertise of database providers like AWS and Fauna is invaluable. Don‘t rack and stack it yourself without good reason.

• Migrate iteratively – Transition existing workloads to serverless in stages. This minimizes risk and allows learnings from smaller proofs of concept.

I hope this guide has provided a helpful overview of the top serverless database options and key selection criteria. Please reach out if you need any advice tailoring these recommendations to your application‘s specific needs. I‘m always happy to help steer you towards the ideal solution.

Wishing you the very best with your product. Please don‘t hesitate to get in touch!