Codync
A free, open-source 1:1 alternative to Grok Bot and Muse. Message Claude Code, Codex, Cursor and 40+ coding agents as persistent bots from your iPhone, Mac or Linux desktop. Group chats, threads, appr
Kafka topics as Iceberg tables: a read-only Iceberg REST catalog and S3 endpoint over any Kafka cluster.
Translation pending
Developer toolsRust · TypeScriptGitHub @PicoMQOnlineOwner unconfirmed
Have you tried it? One tap is enough. No sign-in needed.
No updates detected yet. GitHub releases will appear here.
Owners of public repositories under a personal GitHub account can sign in to verify ownership and manage the introduction themselves. No administrator approval is needed.
Sign in, generate a verification file, and commit it to this repository’s default branch within 30 minutes. Files on other branches or forks do not count. Then check the file below to manage the project without administrator approval. Keep the file to retain your access.
If needed, you will go to sign-in. After signing in, return here and press your chosen verification button again.
Run /nomorevibe verify in your project folder to verify ownership and manage the introduction yourself.
Verify in one minuteAsk about other verification options
Realtime Lakehouse ❤︎ Iceberg Catalog for Kafka
Translation pending
Taken from the repository README
Loading the full README.
Read the full README ↗Mink serves Kafka topics as Iceberg tables, through a read-only Iceberg REST catalog and an S3 endpoint. The records stay in Kafka.
Documentation · Quick start · Contribute
mink/ the node: Kafka client, schemas, Postgres store, Iceberg files and metadata, metrics, and the mink CLIconsole/ the web console, embedded in the nodespecification/ the files and metadata Mink writes(cd console && npm ci && npm run build)
cargo install --path mink/mink-cli
The console is embedded in the binary, so it builds first.
# Kafka, Schema Registry, Postgres and RustFS
docker compose -f harness/compose.yml up -d postgres kafka rustfs schema-registry createbucket
mink serve -c mink.toml
# mink.toml
[kafka]
bootstrap = ["localhost:29092"]
[storage]
endpoint = "http://localhost:9000"
credentials = { access_key_id = "mink", secret_access_key = "minkminkmink" }
[schema_registry]
type = "confluent"
url = "http://localhost:8081"
Catalog on :8181, S3 on :9100, admin API and console on :9180. Every setting has a MINK_* env equivalent.
docker build -t mink .
Running it against the compose stack, and as a cluster: Deployment.
mink table add payments -c mink.toml
mink table list -c mink.toml
mink granularity payments day -c mink.toml
-- DuckDB
INSTALL iceberg; LOAD iceberg; INSTALL httpfs; LOAD httpfs;
CREATE SECRET mink (TYPE S3, KEY_ID 'mink', SECRET 'mink', REGION 'us-east-1',
ENDPOINT '127.0.0.1:9100', URL_STYLE 'path', USE_SSL false);
ATTACH 'warehouse' AS mink (TYPE iceberg, ENDPOINT 'http://127.0.0.1:8181', AUTHORIZATION_TYPE 'none');
SELECT * FROM mink.kafka.payments;
cargo test
# service-backed tests, env-gated
TEST_POSTGRES_URL=postgres://mink:mink@localhost:5432/mink \
TEST_KAFKA_BOOTSTRAP=localhost:29092 \
TEST_S3_ENDPOINT=http://localhost:9000 \
TEST_SCHEMA_REGISTRY=http://localhost:8081 \
cargo test
# end to end in Docker: DuckDB, PyIceberg, Spark, Trino and the console
scripts/e2e.sh