VeltrixDB delivers sub-5ms reads at 1 billion keys — at a fraction of what you pay for Redis, DynamoDB, or Cassandra. One Helm chart. Any cloud. Zero lock-in.
Runs natively on every major platform
Your database was fine at 1 million users. But somewhere between 10M and 100M, things got expensive. Then slow. Then both.
More data means more reads. More reads mean bigger Redis clusters or paying DynamoDB per million operations. The bill grows faster than revenue.
Traditional databases run internal cleanup jobs (compaction) that fight your user requests for disk access. Peak traffic + compaction = your worst nightmare.
Databases without key-value separation rewrite your data over and over. Every unnecessary rewrite is wear on expensive NVMe hardware — and a write amplification tax on your latency.
Great tools — for specific use cases. At 100M+ keys with strict latency SLAs, here's the honest picture.
| What matters to you | Redis | DynamoDB | Cassandra | ★ RecommendedVeltrixDB |
|---|---|---|---|---|
|
🚀 Sub-5ms reads at 1B keys
|
⚠ RAM-limited | ⚠ Varies | ✗ 20–80ms | ✓ Always |
|
💰 Predictable monthly cost
|
⚠ RAM costs scale | ✗ Per-op billing | ⚠ Complex ops | ✓ Fixed infra cost |
|
⚡ No latency spikes under writes
|
✓ Yes | ⚠ Sometimes | ✗ Compaction storms | ✓ Always |
|
📦 Data larger than RAM
|
✗ RAM only | ✓ Yes | ✓ Yes | ✓ NVMe-backed |
|
🔒 No cloud vendor lock-in
|
✓ Self-host | ✗ AWS only | ✓ Self-host | ✓ Any cloud |
|
⎈ Kubernetes-native deploy
|
⚠ Manual config | ✗ Managed only | ⚠ Complex setup | ✓ Helm + Operator |
|
📊 Built-in Prometheus metrics
|
⚠ Basic | ✗ CloudWatch only | ⚠ Plugin needed | ✓ 50+ metrics |
|
🛠️ Simple to operate
|
✓ Simple | ✓ Managed | ✗ Weeks to tune | ✓ 1 Helm chart |
Benchmarked on real cloud hardware — GCP N2 nodes with 8 NVMe SSDs, 64 cores, 480GB RAM.
Lower is better. Measured under sustained mixed read/write load. All databases on equivalent hardware.
VeltrixDB achieves <5ms P99 even on cache misses because values are read directly from NVMe via zero-copy io_uring — no compaction, no page-cache eviction, no surprises.
If your users notice latency and your team notices the bill, this was built for you.
Product catalog, inventory counts, session state, and cart data — serving millions of concurrent users. VeltrixDB handles Black Friday spikes without scaling your bill 10×, because it doesn't require all data in RAM.
Sessions · Inventory · CartsPlayer scores, match state, achievements, and friend lists need millisecond reads across millions of simultaneous players. Sub-5ms at any scale — no lag, no excuses.
Leaderboards · Player State · MatchmakingFraud scoring, rate limiting, and balance lookups need deterministic low latency. A 100ms spike during checkout costs you real money. VeltrixDB delivers predictable <5ms reads even during write bursts.
Fraud Detection · Rate Limits · BalancesModel serving pipelines look up thousands of user features in real time. VeltrixDB's 256GB intelligent cache keeps your hottest features resident — so inference latency is bound by your model, not your database.
Feature Lookup · Embeddings · Model ServingAll the complexity is hidden. You write data, you read data — at any scale — without weekend on-call incidents.
VeltrixDB immediately persists your value to a dedicated fast-write log on NVMe — completely separate from the index. Your write is durable in microseconds, not milliseconds, and never slows down reads.
A 256GB intelligent cache learns which keys you access most. Small, hot keys are never evicted by large cold data — your most important lookups stay in memory, where they cost 0.3ms instead of 4.9ms.
Cache hit: 0.3ms. Cache miss: 4.9ms from NVMe. Background cleanup never competes with your users — it runs on a completely separate I/O path. No compaction storms. No 3 AM pages.
Book a 30-minute demo. We'll benchmark VeltrixDB on your actual workload and show you the numbers — no slides, no fluff, just results.
No commitment · 30-minute session · Free migration analysis included