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Database decision tree

Which AWS Database Should I Use?

Stop scrolling AWS docs. Answer four questions and get a one-screen recommendation with the comparison guide that goes deeper.

Last updated: April 30, 2026 Author: FactualMinds AWS Architects Reviewed by: AWS Solutions Architect — Professional certified

Step 1 / Choose to begin

What does your data look like?

Pick the closest match — we'll narrow further with the next question.

How this decision tree was built

We mapped this tree against the recommendations we make in real architecture reviews. Each leaf links to the comparison guide and service page that go a level deeper. The tree intentionally covers the choices CTOs and senior engineers wrestle with — not every esoteric variant.

If your scenario does not match a clean leaf, the most likely answer is a hybrid: Aurora as the system of record, DynamoDB or ElastiCache for hot paths, and OpenSearch or S3 Vectors for search. That is a common, healthy production shape.

All possible recommendations in this tree

Reference list of every endpoint in this decision tree — useful when you want to skim before answering questions, or when JavaScript is disabled.

Aurora (Provisioned)

Default choice for steady production Postgres/MySQL — better price-perf than RDS, autoscaling storage, and 15 read replicas.

Aurora Global Database

Active-passive or active-active across regions with sub-second cross-region replication — for SaaS that needs disaster recovery or low-latency global reads.

Aurora DSQL

Distributed Postgres with virtually unlimited horizontal scaling and active-active across regions. New for 2025 — best fit when traditional Postgres tops out.

Amazon DocumentDB

MongoDB-compatible managed service. The right migration target if your application already speaks the MongoDB wire protocol and you want managed AWS infrastructure.

Aurora / RDS Postgres with JSONB

Often-overlooked answer. If you already run Postgres and just need a flexible JSON column for semi-structured data, JSONB is great — and you don't need a second database.

Amazon ElastiCache (Valkey / Redis OSS)

In-memory store for sessions, leaderboards, rate limiting, and cache-aside patterns. Sub-millisecond reads when the working set fits in memory.

Amazon Keyspaces (for Apache Cassandra)

Serverless Cassandra. Use only when you have an existing Cassandra workload — for greenfield wide-column use cases, DynamoDB is almost always a better fit.

Amazon Timestream

Purpose-built time-series database with automatic tiered storage. Cheaper than running InfluxDB or Postgres for high-volume telemetry.

Amazon Redshift

Cloud data warehouse. Best fit when time-series queries are part of broader analytics workloads with joins across many tables.

Amazon S3 Vectors or OpenSearch Serverless

Bedrock Knowledge Bases supports both as vector stores. S3 Vectors is the cheapest option for cold/medium-traffic RAG; OpenSearch Serverless wins on hybrid keyword + vector search.

Amazon Neptune

Managed graph database supporting Gremlin, openCypher, and SPARQL. Use when relationships ARE the workload — not as a generic data store.

Frequently Asked Questions

How accurate is this decision tree for production workloads?

It captures the patterns we see across our consulting engagements, but every workload has trade-offs the tree cannot encode (compliance, existing operational expertise, multi-region requirements, etc.). Use it as a starting point, then validate with the linked comparison guides — and book an architecture review if the choice is load-bearing.

Why is DocumentDB ranked behind DynamoDB for greenfield projects?

For new projects, DynamoDB has lower operational cost, better latency at high concurrency, and a more capable serverless billing model. DocumentDB is the right answer mostly when you already have a MongoDB application you want to keep without rewriting.

When should I use Aurora DSQL instead of regular Aurora?

Only when you have outgrown a single Aurora cluster — typically when write throughput requires sharding or you need active-active multi-region writes. Aurora DSQL pricing and operational model is different from Aurora; do a proof-of-concept before committing.

Want a deeper review than the tree?

Send us your workload requirements and we'll write back with a one-page architecture recommendation — usually within two business days.

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