skaidb documentation

skaidb is a leaderless distributed SQL database: every node serves reads and writes, replication is quorum-based with tunable consistency, and clustered UPDATEs are linearizable per row. One binary gives you SQL, secondary/global indexes, full-text search, vector search, geo queries, and time-series storage.

Getting started

Guide What it covers
INSTALL.md Installing from the apt/rpm repo, first start, systemd
DOCKER.md Running in containers
QUERY_SYNTAX.md The complete SQL dialect — DDL, DML, SELECT, transactions, SHOW
HOWDOI.md "How do I…?" — task-by-task code examples in every client language

Using the database

Guide What it covers
INDEXING.md Secondary indexes, planning, covering counts
GLOBAL_INDEXES.md Value-sharded (global) indexes on clusters
SEARCH.md Full-text search: analyzers, hybrid ranking, highlights, suggestions
VECTOR.md Vector/ANN search, quantization, managed embeddings, reranking
GEO.md Geospatial indexing and queries
TIMESERIES.md Time-series tables, rollups, PromQL/remote-write, Prometheus API
PROCEDURES.md Stored procedures: CREATE PROCEDURE, CALL, privileges
MCP.md MCP server: exposing the database to an LLM, and the security model for it

Operating a cluster

Guide What it covers
CLUSTERING.md Membership, replication, consistency levels, witnesses, linearizable UPDATEs
RESHARDING.md Joining/removing nodes, placement changes, data movement
METRICS.md Every Prometheus metric, with alerting hints
GRAFANA.md Dashboards via the scoped Prometheus API
UI.md The built-in web UI
KERBEROS.md GSSAPI/Kerberos authentication (server, clients, REST SSO)
STREAMS.md Change streams: capture, replay and subscribe to matching writes
MQTT.md Native MQTT 3.1.1/5.0 broker (IoT clients, replicated broker state, topic ACLs, topic→table sink)

Reference

Document What it covers
LLM.md The complete machine-readable reference — everything in one file (raw Markdown, made for LLM context windows)
GLOSSARY.md Every abbreviation used in these docs, and what it means here
BENCHMARKS.md Measured comparisons vs PostgreSQL, MongoDB, MariaDB, Elasticsearch