Cachee Demo — 500,000x Faster Cache | 31ns vs 16ms

The Race

Cachee L1 vs ElastiCache on distributed infrastructure. Bars are to scale.

Cachee L1

31ns

ElastiCache

16ms

516,129x

faster — same data, same query

185 years of latency per year at 1B reads/day

At 1 billion reads/day at 16ms per read, your stack accumulates 16 million seconds of latency per day — 185 days. Over a year, that's 185 years of compute time burned on cache round-trips. With Cachee at 31ns per read, the same billion reads take 31 seconds per day — 3.1 hours per year. You get 185 years back. Every year.

It Gets Worse the Farther You Go

Cachee L1 is always 31ns. ElastiCache latency scales with distance.

Topology	ElastiCache	Cachee L1	Faster
Same AZ	339 µs	31 ns	10,935x
Cross-AZ (HA recommended)	1 – 3 ms	31 ns	32,258 – 96,774x
Cross-Region	30 – 80 ms	31 ns	967,741 – 2,580,645x
Public Internet / VPN	50 – 150 ms	31 ns	1,612,903 – 4,838,709x

Try Commands Redis Can't Do

Every response shows real latency. Copy any command into your own environment.

cachee-cli — demo.cachee.ai:6380

cachee> SET user:1 alice

OK (548ns)

cachee> SET user:1 bob

OK (548ns)

cachee> GET_AT user:1 1711670400000

"alice" (31ns) Redis: impossible

Read any key at any point in time. Full version history. Debug production issues by rewinding your cache.

cachee> MVCC_READ user:1 1

"alice" (31ns) Redis: impossible

Snapshot isolation. Readers never block writers. Long analytics queries see consistent state while production writes continue.

cachee> DEPENDS_ON user:1:cache user:1

(integer) 1 (548ns)

cachee> CASCADE user:1

1) "user:1:cache" (31ns) Redis: impossible

Change a source record, all derived cache keys auto-invalidate. No more stale data from forgotten cache keys.

cachee> CONTRACT SET pricing 5000 https://api.example.com/price 10000

OK (548ns) Redis: impossible

Freshness SLA: this key auto-refreshes at 80% of the 5s deadline. If refresh fails, serve stale with grace period. Compliance-grade guarantees.

Cross-Instance Coherence

Two Cachee instances. Write to one. Watch the other invalidate in real time. Sub-millisecond.

Instance A (us-east-1a)

$ SET product:42 "$99.99"

OK (548ns)

$ SET product:42 "$89.99" ← price change

OK (548ns)

PUBLISH cachee:invalidate product:42 (auto)

→

Instance B (us-east-1b)

L1 cache: product:42 = "$99.99"

... serving requests at 31ns ...

RECV invalidate product:42 (0.3ms)

L1 evict product:42

Next GET → L2 fetch → "$89.99" (0.5ms)

0.3ms cross-instance invalidation

No stale data. No manual cache busting. No distributed lock contention. Every Cachee instance subscribes to cachee:invalidate. Write anywhere, consistency everywhere. This is the demo that closes enterprise deals.

Simulate Your Workload

Paste your key access patterns. We'll show you the latency difference.

Your cache key patterns (one per line)

Example: user:{id}:profile, session:{token}, product:{sku}:price, cart:{uid}:items

Simulated Results (100K requests/sec)

Keys analyzed —

ElastiCache total latency/sec —

Cachee total latency/sec —

Latency saved per second —

Latency saved per day —

Estimated hit rate (hot keys) —

Things Redis Literally Cannot Do

Not "hasn't implemented yet." Architecturally impossible over a network hop.

⏪

Time-Travel Reads

GET_AT key timestamp

Read any key's value at any point in time. Full version history. Git for your cache.

Redis: no versioning

🔀

Snapshot Isolation

MVCC_READ key epoch

Readers never block writers. Consistent snapshots. Zero lock contention.

Redis: single-threaded, no MVCC

🧠

Vector Similarity

VSEARCH key dims... K

HNSW nearest-neighbor search. Cosine, L2, dot product. Metadata filters.

Redis: requires RediSearch module

🌳

Dependency Cascade

CASCADE source_key

DAG invalidation. Change a source, all dependents auto-invalidate.

Redis: no dependency tracking

📋

Freshness Contracts

CONTRACT SET key ms url

Per-key SLA. Auto-refresh at 80% of deadline. Degrade policies.

Redis: TTL or nothing

🔮

Speculative Prefetch

PREFETCH_PREDICT key N

Learns access patterns. Predicts next keys. Pre-warms before you ask.

Redis: no pattern learning

31ns cache reads.
Not 16ms.

The Race

It Gets Worse the Farther You Go

Try Commands Redis Can't Do

Cross-Instance Coherence

Instance A (us-east-1a)

Instance B (us-east-1b)

Simulate Your Workload

Simulated Results (100K requests/sec)

Things Redis Literally Cannot Do

Time-Travel Reads

Snapshot Isolation

Vector Similarity

Dependency Cascade

Freshness Contracts

Speculative Prefetch

Your cache at 31ns. Today.

31ns cache reads.Not 16ms.

The Race

It Gets Worse the Farther You Go

Try Commands Redis Can't Do

Cross-Instance Coherence

Instance A (us-east-1a)

Instance B (us-east-1b)

Simulate Your Workload

Simulated Results (100K requests/sec)

Things Redis Literally Cannot Do

Time-Travel Reads

Snapshot Isolation

Vector Similarity

Dependency Cascade

Freshness Contracts

Speculative Prefetch

Your cache at 31ns. Today.

31ns cache reads.
Not 16ms.