When should I use Cloudflare D1 over KV?

Use D1 when you need relational queries (JOINs, WHERE clauses, aggregations), complex filtering, or ACID transactions. D1 is a full SQL database (SQLite). Use it for user data, form submissions, analytics, content management, and anything requiring structured queries.

When should I use Cloudflare KV over D1?

Use KV for simple key-value lookups where you know the exact key. It's globally distributed with sub-millisecond reads. Perfect for: session tokens, feature flags, cached API responses, configuration values, and any read-heavy workload with infrequent writes.

Can I use both D1 and KV in the same project?

Yes, and you should. A common pattern: D1 as your source of truth (writes go here), KV as a read-through cache (cached reads for frequently accessed data). This gives you both query flexibility and read performance.

Cloudflare Database Architecture

Cloudflare D1 vs KV — When to Use What

15 July 2026 5 min read

Cloudflare gives you two storage options: D1 (SQL database) and KV (key-value store). They solve different problems. Here's when to use each — based on real patterns from our production applications.

At a Glance

Feature	D1	KV
Type	Relational (SQLite)	Key-value store
Query language	Full SQL	get/put/list/delete
Read latency	5-30ms	<1ms (cached)
Write latency	~30ms	~500ms (eventual)
Consistency	Strong (single region)	Eventually consistent
Best for	Structured data, queries	Caching, sessions, flags
Free tier	5M reads/day, 100K writes	100K reads/day, 1K writes

Use D1 When...

You need to query by multiple fields: "Show me all emails where category='contact' AND read=0 ORDER BY created_at DESC LIMIT 20" — this is SQL territory.

You need aggregations: COUNT(*), SUM, AVG, GROUP BY — analytics, reporting, leaderboards.

You need relationships: Users have posts, posts have comments — foreign keys, JOINs.

You need strong consistency: A write must be immediately visible to the next read (financial data, counters, sequences).

Use KV When...

You know the exact key: Session lookup by token, feature flag by name, user preference by UUID — O(1) access.

Reads massively outnumber writes: Config values, cached API responses, static content that rarely changes.

You need global low-latency reads: KV replicates globally. Sub-millisecond reads from anywhere in the world.

You need TTL expiration: Temporary data like rate limit counters, cache entries, or OTP tokens that auto-delete.

The Combined Pattern (Best of Both)

💡 Our Production Pattern

Write to D1 (source of truth) → Cache the result in KV with a TTL → Reads hit KV first (fast) → If KV misses, query D1 (slower but always fresh) → Update KV with the result. This gives you SQL query power with global KV read speed.

On ScrabbleWordsFinder, we use D1 for all structured data (emails, clicks, games, leaderboards, rankings) and KV for admin session tokens and cached API responses.

Real Examples from Our Projects

Contact form → D1

Structured data, filterable by category/status, editable via admin CRUD.

Admin session → KV

Lookup by session token, TTL expiration (7 days), global availability.

Click analytics → D1

20-field records, GROUP BY queries, time-series filtering, aggregation.

Crypto prices → KV

Cached API response with 30-second TTL. Fast reads, infrequent updates.

Building on Cloudflare?

We architect and deploy full-stack applications on Cloudflare's edge. D1, KV, Workers AI — the full stack.

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