# ByConity/ByConity

ByConity is an open source cloud data warehouse

Repository: https://github.com/ByConity/ByConity
Canonical: https://ross.abutalabs.com/products/byconity
Homepage: https://byconity.github.io/
Language: C++
License: Apache-2.0
License Family: permissive
Topics: clickhouse, cloud, kubernets, lakehouse, olap, s3, snowflake, sql, clickhouse-database, tiktok, bytedance
Archived: true
Last push: 2026-06-14T02:35:45+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 87, release rhythm 40, longevity 96
- inputs: {"age_days": 1350, "days_push": 81, "days_rel": 646, "gap_med": 24, "n_releases_24m": 2}
- flags: archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2239, forks 310 (observed 2026-08-28T04:06:29.656566+00:00)

## What it is
ByConity is an open-source cloud-native distributed SQL data warehouse built on the ClickHouse 21.8 codebase, developed by ByteDance/Volcano Engine. It targets interactive and ad-hoc analytical queries at massive scale with storage-compute separation and deployment on Kubernetes with S3 object storage. The project has been retired: it entered a transition period on June 1, 2026, and the repository will be archived read-only after August 1, 2026, with no new features, bug fixes, or security patches thereafter.

## Use cases
- run a cloud-native OLAP data warehouse on Kubernetes with S3 storage
- serve sub-second interactive and ad-hoc analytical queries over massive datasets
- unify offline batch and real-time streaming data ingestion for analytics
- query a ClickHouse-compatible warehouse with tools like Superset and Tableau
- perform multi-table associative analytical queries with a CBO/RBO optimizer
- self-host a Snowflake-like lakehouse analytics engine

## When to choose
- you already run ByConity and need to keep an existing deployment stable through migration
- you need a ClickHouse-compatible engine with storage-compute separation and can accept an unmaintained codebase
- you are studying cloud-native data warehouse architecture for research or reference

## When to avoid
- you need a actively maintained data warehouse with security patches and new features
- you are starting a new analytics project with no existing ByConity investment
- you require long-term community support or a one-to-one open-source replacement

## Facets
- artifact type: application
- maturity: abandoned
- function: database, search-engine, etl, streaming
- domain: databases, big-data, analytics, cloud-computing
- platform: self-hosted, cpp
- tags: olap, data-warehouse, clickhouse-fork, lakehouse, s3, columnar-storage, sql, end-of-life, data-engineering, linux, docker, kubernetes

## Member repositories
- ByConity/ByConity (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:29.656566+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:44:08.672449+00:00, confidence not recorded.
  - readme: https://github.com/ByConity/ByConity (fetched 2026-08-28T04:06:29.656566+00:00, sha 4a86cb96346b)
  - homepage: https://byconity.github.io/ (fetched 2026-08-29T10:24:28.294877+00:00, sha aea5b0edf503)
- Data as of 2026-08-30T08:39:29.467469+00:00.