kdbx

KDB-X

Unified compute engine: time-series analytics + vector search + GPU-accelerated compute in one runtime. GA April 2026. Multi-language (q, Python, SQL), native Parquet/Arrow, 25+ community modules. Community Edition free at developer.kx.com.

When to Use

Need	Skill
KDB-X modules, AI libs, Parquet, kURL, GPU, objstor	This skill
q language syntax, operators, table queries	/q
PyKX Python-to-kdb+ integration	/pykx
KDB.AI cloud vector database	/kdbai
kdb Insights enterprise platform	/kdb-insights

Module Loading

Always use, NEVER \l (\l doesn't bind native functions):

.pq:use`kx.pq              / Parquet        .pq.t:use`kx.pq.t  / Virtual tables
.kurl:use`kx.kurl           / REST client    .ai:use`kx.ai       / AI libraries
.gpu:use`kx.gpu             / GPU accel      .objstor:use`kx.objstor / Object storage
.rest:use`kx.rest           / REST server

Parquet

trades: pq `:trades.parquet                       / Virtual table (row-group pruning)
select from trades where date > 2024.01.01
meta: op `:data.parquet                           / File metadata
vt: (.pq.t:use`kx.pq.t)[`tt] tbl                 / Wrap kdb+ table as virtual

Compression: snappy, gzip, brotli, lz4, zstd.

kURL REST Client

/ .kurl.sync (url; method; options) -> (statusCode; body)
resp:.kurl.sync ("https://api.example.com/data"; `GET; ::)
resp:.kurl.sync ("https://api.example.com"; `POST; enlist[`body]!enlist .j.j data)
resp:.kurl.sync ("https://s3.example.com/f"; `PUT; enlist[`file]!enlist `:path/to/file.csv)
opts:`headers`body!(("Content-Type";"x-api-key")!("application/json";"key123"); .j.j data)
.kurl.async ("https://api.example.com/data"; `GET; enlist[`callback]!enlist (`;{show x}))

/ Auth: .kurl.init`aws then .kurl.register (type; domain; tenant; info)
/ Types: `aws_cred`aws_sts`oauth2`oauth2_jwt`azure`basic
.kurl.aws.registerByCredentialsFile `:~/.aws/credentials  / or register manually

Options: `headers`body`file`callback`service`region

Object Storage

.objstor.init[]                                / Register all vendors (or .objstor.init`aws)
/ URI schemes: :s3://  :ms://  :gs://  — standard kdb+ file ops work:
hcount `$":s3://bucket/path/file"              / read1, key, get also work

Env vars: AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_REGION, AZURE_STORAGE_ACCOUNT, AZURE_STORAGE_SHARED_KEY, GCP_TOKEN. S3-compatible: KX_S3_ENDPOINT.

AI Libraries

Index	Namespace	Use Case
HNSW	.ai.hnsw	Fast approximate search (default)
Flat	.ai.flat	Exact search, small datasets
IVF	.ai.ivf	Large-scale partitioned
IVFPQ	.ai.pq	Compressed, memory-constrained
BM25	.ai.bm25	Text/keyword search
Fuzzy	.ai.fuzzy	Approximate string match
Hybrid	.ai.hybrid	Vector + BM25 via RRF
TSS	.ai.tss	Time series similarity + anomaly
DTW	.ai.dtw	Dynamic time warping

/ HNSW (most common): embs and hnsw are SEPARATE objects
vecs:{(x;y)#(x*y)?1e}[1000;10]
hnsw:.ai.hnsw.put[();();vecs;`L2;32;1%log 32;64]
res:.ai.hnsw.search[vecs;hnsw;first vecs;5;`L2;32]   / metric MUST match put
merged:.ai.hybrid.rrf[(vecResults; bm25Results); 60]   / RRF fusion

Full API signatures: See ai-reference.md

GPU Acceleration

T:.gpu.to trades                              / Move to GPU (all columns)
T:.gpu.xto[`price`size] trades                / Mixed residency
.gpu.select[T;enlist(=;`sym;enlist`AAPL);0b;()]  / GPU qSQL (functional select)
.gpu.aj[`sym`time; Trade; Quote]              / GPU as-of join (needs `g#)
.gpu.xasc[`time] T                            / GPU sort

Requires NVIDIA data center GPUs, CUDA 13.1, driver v590+. 10x-25x speedups, near-linear multi-GPU scaling. Full API: See gpu-reference.md

Multi-Language

select avg price by 5 xbar time from trades where sym=`AAPL     / q
s)SELECT AVG(price) FROM trades WHERE sym='AAPL' GROUP BY time/5 / SQL

Common Errors

Error	Cause	Fix
nyi	\l instead of use	.mod:use\kx.mod`
module not found	QHOME not set	getenv\QHOME`
length on search	Dim mismatch	count queryVec must match index
Wrong results	Metric mismatch put/search	Same metric in both
rank on search	Empty index	Verify data populated
type on hnsw.put	Wrong vector type	Cast to real

MCP Tools

• mcp__qmcp__connect_to_q — Connect to KDB-X
• mcp__qmcp__query_q — Execute queries

User Request: $ARGUMENTS