Your matching engine runs in nanoseconds. Your FPGA NICs process packets in nanoseconds. But your cache layer adds 1,000,000 nanoseconds per lookup. Cachee eliminates 93% of that latency -- delivering market data, order state, and risk checks at 17ns.
Start Free Trial →Trading systems are measured in microseconds. Your matching engine runs in nanoseconds. Your FPGA NICs process packets in nanoseconds. But every time you query Redis for market data or order state, you pay 1,000,000 nanoseconds of latency. The cache layer -- the one component every request touches -- is the slowest link in the chain.
Cachee replaces the Redis/Memcached layer in every latency-critical data path. Same API. No application rewrites. Just 59,000x less latency.
Cache L1/L2/L3 book state, NBBO, and trade prints. Every subscriber reads from in-process memory instead of hitting a centralized cache cluster. Eliminates fan-out bottleneck.
Full depth-of-book snapshots cached at the process level. Price levels, quantities, and order counts available in a single 17ns lookup. No network round-trip for every price check.
Position limits, exposure calculations, and credit checks sourced from L1 cache. Risk gates that previously added 1ms+ of latency per check now complete in nanoseconds.
Historical and real-time bar data cached for signal generation. Quant models read from memory-speed cache instead of waiting on time-series databases or Redis clusters.
FIX session state, API tokens, and entitlements cached in-process. Authentication checks that touched Redis on every request now resolve in 17ns.
Venue latency tables, fill rates, and rebate schedules cached for instant SOR decisions. Route selection that queried external state now runs at memory speed.
All benchmarks run on production hardware. Independently reproducible. No synthetic best-case scenarios.
| Operation | Cachee | Redis | Delta |
|---|---|---|---|
| GET (single key) | 17 ns | 1.0 ms | 59,000x faster |
| SET (single key) | 22 ns | 1.1 ms | 50,000x faster |
| Throughput (ops/sec) | 59M | ~250K | 236x higher |
| P99 Latency | 24 ns | 2.5 ms | 104,000x faster |
| Hit Rate | 98.1% | ~95% | 3.1% miss vs 5% |
Cachee deploys as a sidecar or embedded library. It intercepts cache calls at the application layer -- before they ever hit the network. Redis remains your backing store for persistence and replication. Cachee is the L1 that sits in front of it.
Hot keys live in the application's own memory space. No network hop. No serialization. Direct pointer access at 17ns.
Cross-process shared cache for multi-instance deployments. Sub-microsecond access without network traversal.
Your existing Redis, Valkey, or Memcached cluster. Cachee falls through to L3 on cold misses and backfills L1/L2 automatically.
A typical trading system makes 5-15 cache lookups per order lifecycle. With Redis, that is 5-15ms of cache latency alone. With Cachee, it is 85-255 nanoseconds.
| Order Lifecycle Step | Cache Lookups | Redis Cost | Cachee Cost |
|---|---|---|---|
| Market data check | 2 | 2.0 ms | 34 ns |
| Pre-trade risk validation | 4 | 4.0 ms | 68 ns |
| Order routing decision | 3 | 3.0 ms | 51 ns |
| Position update | 2 | 2.0 ms | 34 ns |
| Post-trade reporting | 3 | 3.0 ms | 51 ns |
| Total per order | 14 | 14.0 ms | 238 ns |
Signal generation pipelines that read thousands of market data points per decision cycle. Every Redis round-trip is a lost alpha opportunity.
Continuous quoting requires instant access to position state, risk limits, and venue latency tables. 17ns means tighter spreads and faster requotes.
SOR, DMA, and algo execution engines where cache latency directly impacts fill rates and slippage. Cachee removes the network from the critical path.
Matching engines, wallet state, and order book snapshots at memory speed. Support 59M ops/sec without a cache cluster scaling problem.
Start a free trial with 1M requests. No credit card. Full performance from day one.