Directory Data & AnalyticsDatabase PlatformsFauna

Fauna

About Fauna

Fauna provides a globally distributed, serverless database platform designed to simplify application development and data management for enterprises. It offers a transactional, consistent, and highly available database service that eliminates the operational complexity of traditional databases. Fauna is built to support modern application architectures, including microservices and serverless functions, enabling developers to focus on building features rather than managing infrastructure.

Targeted at enterprise organizations requiring scalable, secure, and low-latency data solutions, Fauna supports multi-region deployments with strong consistency guarantees. Its flexible query language and native support for GraphQL APIs allow seamless integration with modern development workflows. The platform’s primary value lies in its ability to deliver a fully managed, globally consistent database experience that reduces operational overhead while ensuring compliance and security standards suitable for enterprise environments.

How to evaluate Database Platforms

This is how the CIOPages Research Team evaluates this category. It is not an assessment of Fauna. It comes from our Enterprise Database Platforms buyer guide.

25%

Data Model & Query Fit

Match of the engine to the workload: relational integrity and joins, document/JSON flexibility, key-value latency; transaction isolation levels and ACID guarantees; SQL standard coverage and dialect quirks; secondary indexes, full-text and vector (pgvector / Atlas Search) support; foreign keys and referential integrity where you need them

20%

Consistency, Scale & HA

Single-primary vs. multi-writer; synchronous vs. async replication and resulting RPO; read-replica and sharding story; horizontal write scale and global/multi-region behavior (strong vs. eventual consistency); failover time, achievable RTO, and how partitions are handled under load

20%

Operability & Managed-Service Experience

Quality of the managed offering (RDS/Aurora, Azure SQL, Cloud SQL/AlloyDB) vs. self-managed burden; in-place and major-version upgrade path; backup/PITR, observability, and connection pooling; autoscaling and serverless options; day-2 toil — vacuum/compaction, index bloat, rebalancing — and the depth of the DBA skills it demands

15%

Licensing & Portability

License class and its real constraints: OSI open source (PostgreSQL, MySQL, Valkey, Redis 8 AGPL) vs. source-available (MongoDB SSPL, CockroachDB enterprise/BSL) vs. proprietary (Oracle, SQL Server); cloud lock-in of proprietary engines (Aurora, Spanner, DynamoDB); wire-protocol and SQL-dialect compatibility that preserves an exit; audit exposure on proprietary metrics

12%

Security & Compliance

Encryption at rest and in transit, TLS enforcement, and key management (BYOK/HSM); row- and column-level security and fine-grained RBAC; field-level / queryable encryption for sensitive data; audit logging; data-residency controls and certifications (SOC 2, ISO 27001, HIPAA, PCI, FedRAMP) on the managed service

Ecosystem & Talent

Driver and ORM maturity across your languages; migration and CDC tooling (logical replication, Debezium, DMS); breadth of extensions and integrations; size and hireability of the talent pool; quality of docs and the support path — first-party vendor vs. third-party (EDB, Percona, Crunchy) for open engines

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