Cachee for Gaming Infrastructure

128-Tick Servers.
Zero Tick Budget Wasted on State Reads.

At 128Hz, your server has 7.8ms per tick to read game state, run physics, simulate the world, and send updates to 100 players. Standard state reads (Redis, shared memory at 1–10μs per object) consume 40–60% of that budget. Cachee serves player positions, health, inventory, and world state from L1 cache at 17ns — giving 99% of the tick budget back to your simulation.

Riot GamesEpic GamesValveActivision BlizzardEA DICEUbisoftAWS GameLiftUnityNVIDIA GeForce NOW

7.8ms

Tick Budget @ 128Hz

every millisecond matters

3.2B

Active Gamers

55M peak concurrent

$11B+

Cloud Gaming (2025)

46.9% CAGR

17ns

State Object Read

vs 1–10μs standard

Live Server Tick Simulation

Watch How State Reads Eat Your Tick Budget

Each tick, the server reads state for every player and world object, runs physics, simulates the game, then sends updates. The tick budget bar shows exactly where the time goes.

🔴 Standard Server (Redis/Shared Mem)μs reads

Tick Budget: 7.8ms0%

0ms

State Reads

0ms

Physics + Sim

0ms

Network Send

Tick budget used:—

🟢 Cachee-Enhanced Server (L1)ns reads

Tick Budget: 7.8ms0%

0ms

State Reads

0ms

Physics + Sim

0ms

Network Send

Tick budget used:—

Ticks Simulated

Std Tick Overruns

Cachee Overruns

Avg Cachee Headroom

Extra Players Possible

The Tick Budget Crisis

Your Simulation Is Fast. Your State Reads Aren't.

Game engines are incredibly optimized — physics, collision, AI all run in microseconds. But every tick, the server must also read the current state of every relevant object. At 128Hz with 100 players, that's 10,000–50,000 state reads per second. This is where the budget disappears.

🎯

Player State Reads

Position, velocity, health, armor, ammo, weapon state, ability cooldowns, team, status effects — each player has 15–30 state properties. At 100 players × 20 properties × 128 ticks/sec = 256,000 reads/sec. At 5μs per Redis read, that alone consumes 1.28 seconds of compute per second.

256K reads/sec per server

🌍

World Object State

Destructible environment, dropped items, vehicles, AI NPCs, projectiles — a typical FPS map has 500–2,000 dynamic objects. Each needs position and state read per tick. That's another 128K–256K reads/sec on top of player state, and these objects interact with physics.

500K+ total reads/sec

⚡

Tick Overrun = Rubber-Banding

When state reads push total tick time past the budget (7.8ms at 128Hz), the server drops to a lower effective tick rate. Players experience rubber-banding, hit registration failures, and desync. In competitive games, this is catastrophic — tournaments have been paused over tick rate drops.

128Hz → 64Hz on overrun

The Transformation

From Overrun to Headroom. Every Tick, Every Server.

Redis / Shared Memory

4.2ms

state read time per tick (128Hz, 100 players)

Player state (100×20)2.0ms

World objects (1,000)1.5ms

Physics + sim2.5ms

Network serialize1.2ms

Total per tick7.2ms / 7.8ms

Headroom8% ⚠️

→

Cachee L1 Cache

0.05ms

state read time per tick (128Hz, 100 players)

Player state (100×20)34μs

World objects (1,000)17μs

Physics + sim2.5ms

Network serialize1.2ms

Total per tick3.75ms / 7.8ms

Headroom52% ✅

Architecture

Drop Into Your Game Server. Zero Engine Changes.

ECS-Native State Store

Cachee maps directly to Entity-Component-System architectures. Each component (Transform, Health, Inventory) is stored contiguously in L1-cached arrays. Iteration over all entities for a given component hits L1 on every access — perfect for the tight loops game servers run 128 times per second.

Predictive State Warming

ML model trained on player behavior predicts which game objects will be needed next tick (line-of-sight, proximity, weapon range). Pre-loads their state to L1 before the tick begins. Prediction accuracy improves with game-specific training — FPS patterns differ from MMO patterns.

Spatial Partitioning in L1

Game worlds use spatial structures (octrees, BSP, grid) to limit state reads to nearby objects. Cachee pre-loads spatial partitions based on player positions — only objects in relevant cells are in L1. Reduces effective reads from 50,000 to 5,000 per tick while maintaining full world fidelity.

Cloud Gaming Frame Pipeline

For cloud gaming (GeForce NOW, Xbox Cloud), the render server must read game state, render the frame, encode it, and stream it — all within 16.6ms (60fps). Cachee's 17ns state reads mean the renderer starts work 4ms sooner, reducing total input-to-photon latency from 50ms to 46ms.

The Business Case

More Players Per Server. Higher Tick Rates. Lower Infrastructure.

2–3× Players Per Server

With 52% tick budget headroom, double player density or double tick rate

52%

Tick budget headroom
vs 8% standard

-50%

Server infrastructure
at same player count

Zero

Tick overruns
no rubber-banding

128→256

Tick rate upgrade
possible with headroom

For a game running 10,000 servers: If Cachee enables 2× player density per server, you need 5,000 servers instead of 10,000. At $0.50–$1.00/hr per game server instance (AWS GameLift pricing), that's $22M–$44M/year in infrastructure savings. Or: keep 10,000 servers and upgrade from 64-tick to 128-tick — giving every player a competitive-grade experience.

For esports / competitive: Valorant runs at 128-tick because Riot Games knows tick rate is a competitive advantage. But maintaining 128-tick under load (tournament play with observers, replays, analytics) is brutally expensive. Cachee ensures 128-tick never drops — even during the most intense teamfights with maximum entity count.

128-Tick Servers.Zero Tick Budget Wasted on State Reads.

128-Tick Servers.
Zero Tick Budget Wasted on State Reads.