KDB.AI
A vector database designed for generative AI applications that combines vector search with time-series data capabilities
- Vendor
- KX
- Also known as
- kdb-ai
What is KDB.AI?
KDB.AI is a specialized vector database enabling developers to build AI-powered applications by integrating vector embeddings with structured time-series data. It supports hybrid search, multimodal retrieval, and real-time analytics for generative AI and RAG applications.
KDB.AI pricing
Plans, per-tier features and add-ons, dated and linked to live pricing. Pricing changes often; always verify at source before you rely on it.
Free tier available; enterprise pricing via contact sales
Free
FreeWhat KDB.AI does
The capabilities that matter for vector databases, normalised so it lines up with every alternative. “-” means we haven't confirmed it, not that it's missing.
- Deployment
- Managed
- Serverless / consumption pricing
- -
- ANN index (HNSW / IVF / DiskANN / ScaNN / flat)
- Flat, qFlat, IVF, IVFPQ, HNSW, qHnsw
- Distance metrics (cosine / dot / Euclidean)
- Euclidean, Inner-Product, Cosine
- Metadata filtering
- Pre-filter
- Hybrid search (dense + sparse fusion)
- ✓
- Built-in BM25 / lexical
- ✓
- Quantization
- Product
- On-disk vs in-memory
- Disk-backed
- Multi-tenancy (namespaces / collections / tenants)
- ✓
- Horizontal scale
- Sharded / distributed
- Consistency
- -
- Licence class
- -
- Purpose-built vs feature-of-parent
- Dedicated DBMS
Platform & deployment
Independently observed- Cloud / SaaS
- On-premise
Integrations (8)
Independently observed- Hugging Face
- NVIDIA cuVS
- LlamaIndex
- Langchain
- Voyage AI
- TwelveLabs
- Google Colab
- HuggingFace
KDB.AI FAQ
Common questions about KDB.AI, answered from independent, dated evidence.
What is KDB.AI?
A vector database for contextual and time series search that enables building AI apps, finding patterns in data, and mixing structured with unstructured data. It is indexed under Vector Databases.
Source: https://kdb.ai
Is KDB.AI free?
KDB.AI offers a free tier, so you can start without paying. Pricing changes often, so verify at source before relying on it.
Source: https://kdb.ai
Can KDB.AI be self-hosted?
Yes. KDB.AI can be deployed cloud / SaaS, on-premise and self-hosted, so it does not have to run on the vendor's infrastructure.
Source: https://kdb.ai
What does KDB.AI integrate with?
We have confirmed 7 integrations for KDB.AI, including Hugging Face, NVIDIA cuVS, LlamaIndex, Langchain, Voyage AI, TwelveLabs and Google Colab. This is what we could verify from public sources, so the vendor may support others we have not indexed.
Source: https://kdb.ai
KDB.AI alternatives
Other vector databases we track, ranked by the same independent score.
- Zilliz CloudA fully managed cloud service for storing, indexing, and searching high-dimensional vector data at scalemedium · 74%
- PineconeManaged vector database infrastructure for machine learning applicationshigh · 75%
- TurbopufferA database combining vector similarity and text search built on cloud storagemedium · 61%
- EpsillaCreate AI agents without needing engineering resourceslow · 30%
- Chromamedium · 70%
- WeaviateA vector database platform designed for building AI-powered semantic search applicationshigh · 75%
Compare KDB.AI
Side by side against other vector databases, attribute by attribute, with a source on every value.
The vioscaleAI score: one lens on the evidence
Not user reviews and not a paid placement: a confidence-weighted blend of the independent signals below (adoption, activity, security posture, and more), which you can sort and re-weight yourself. Vendors can correct their listing but can never move their rank, and stars are weighted low as a vanity metric. It is one way to read the evidence for KDB.AI, not the verdict.
| Signal | Score | Weight | Contribution | Evidence |
|---|---|---|---|---|
| Price level | 80 | 0.04 | 3.3 | ✓ |
| Capabilities | 58 | 0.04 | 2.2 | ✓ |
| Pricing transparency | 25 | 0.05 | 1.4 | ✓ |
| Integrations | 22 | 0.04 | 1.0 | ✓ |
| Reliability | 0 | 0.07 | 0.0 | - |
| Security posture | 5 | 0.12 | 0.0 | - |
Computed . Re-weight it by intent, or see the full method.
All data & sourcesshow ↓
Every value we hold, with its source, retrieval date, and confidence. This is the evidence behind the score: don't trust it, verify it.
Content
| Attribute | Value | Evidence |
|---|---|---|
| Faq | 4 items | mediumsource · 2026-09-10 · 60% |
Features
| Attribute | Value | Evidence |
|---|---|---|
| Capabilities | Ann index: Flat, qFlat, IVF, IVFPQ, HNSW, qHnsw · Deployment: managed · Quantization: product · Storage tier: disk_backed · Hybrid search: Yes · Multi tenancy: Yes | mediumsource · 2026-09-18 · 60% |
Integrations
| Attribute | Value | Evidence |
|---|---|---|
| Count | 5 | mediumsource · 2026-09-18 · 60% |
Pricing
Security
| Attribute | Value | Evidence |
|---|---|---|
| Disclosure policy | Yes | mediumsource · 2026-08-03 · 60% |
Is KDB.AI the right choice for you?
Tell us the job, the constraints and what you weigh most, and we will rank KDB.AI against the rest of the vector databases we index, using the same dated evidence weighted your way.
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