Sub-2ms Pre-Filtered
Vector Search at Planet Scale.
MassEngine is a next-generation kNN vector database built from the ground up for multi-tenant AI & RAG systems. Eliminate selective-filter latency cliffs while cutting cluster memory footprints by 7×.
No Filter Cliffs. No Memory Bloat.
Evaluated on an identical 2-node replicated cluster (RF=2, 8 Shards, 2,000,000 × 1024-d English Wikipedia BAAI/bge-m3 embeddings, 10 concurrent clients). Select a filter selectivity below to compare throughput, latency, and memory:
Everything Modern RAG Needs in One Engine
Replace fragile multi-system pipelines with a single, deterministic search layer.
True Multi-Tenant Isolation
Host thousands of customer workspaces on shared infrastructure with zero noisy-neighbor degradation, scoped RBAC API keys, per-tenant QoS rate limits, and instant GDPR tenant purge.
High-Throughput Reads & Writes
Ingest over 72,000 vectors/sec with instant availability while sustaining up to 6,993 filtered QPS and sub-millisecond query latency under concurrent production load.
Rich Metadata Pre-Filtering
Filter on arbitrary JSON attributes using expressive operators ($eq, $ne, $gte, $lte, $in, $contains), date ranges, and category bitmaps with zero recall penalty.
In-Place Metadata Patching
Update document permissions, pricing, tags, or categories in place via PATCH without re-computing or re-uploading expensive high-dimensional embeddings.
Flexible Dimension Support
Native support for any embedding model dimension—from compact 128-d and 384-d models up to 1536-d and 3072-d frontier embeddings.
1-Click AWS & GCP Clusters
Start free with a 1-Core Developer License (up to 1M vectors), or purchase a signed Ed25519 per-core license (meli_...) and launch a multi-node HA cluster directly inside your own AWS or GCP VPC in 1 click.
Clean REST & SDK Interface
Simple, predictable JSON APIs and typed SDKs for Go, Python, and TypeScript.
POST https://api.massengine.com/v1/search
Authorization: Bearer mk_live_9f8a7b6c...
Content-Type: application/json
{
"vector": [0.021, -0.044, 0.089, "... 1024 dims"],
"k": 10,
"nprobe": 16,
"rerank_pool": 64,
"min_score": 0.75,
"metadata_filter": {
"department": { "$in": ["security", "legal"] },
"clearance_level": { "$gte": 2 },
"tags": { "$contains": "approved" }
}
}
Same 20M Records. 3 Live Hardware Setups.
See how MassEngine serves the exact same 20,000,000 English Wikipedia passages (1024-d embeddings, 83.46 GiB logical corpus across 8 shards) across three distinct live hardware profiles with 100% Top-K recall parity.
2-Node High-End In-Memory
All 8 shards (RF=2) pinned in high-bandwidth RAM for ultra-low tail latency under heavy concurrent load.
2-Node High-End NVMe
Identical 20M-record dataset served on a strict memory cap with zero-copy mmap NVMe segment tiering.
4-Node Low-End NVMe
20,000,000 vectors distributed across 4 lightweight nodes (1 vCPU / 6.8 GiB RAM each) backed by NVMe storage.
1-Core Free Forever. Scale with Floating Per-Core Licenses.
Deploy MassEngine on any cloud or bare-metal hardware (AWS, Google Cloud, Azure, Docker, or On-Prem Linux) with a signed per-core license key (meli_...)—with no memory or disk storage limits. Testing or prototyping? Your first core is free forever.
1-Core Developer — $0 / mo
Instant activation in the Cloud Console. Run on your laptop, Docker, or any cloud VM for development, evaluation, and workloads up to 1,000,000 vectors.
Per-Core License — $99 / core / mo
Pick your number of nodes and cores per node. Scale out or scale up anytime across your floating core pool with no memory or storage surcharges.
Need enterprise volume licensing, custom invoicing, or architecture guidance? Reach out via the Enterprise form below ↓
Contact Enterprise Engineering
Planning an In-VPC deployment or 100M+ vector cluster? Reach out below—or create a self-service Cloud Console account to start immediately.