The bucket is the coordinator — no membership protocol, no failure detector, no consensus. Ownership is a record in your bucket, claimed with one atomic write. celld's built-in replicator continuously ships each cell's SQLite state to that bucket as LTX segments.
celld: Durable Objects, self-hosted
celld is an open-source daemon that runs a Cloudflare Workers application on your own machines, including Durable Objects, KV, Queues, D1, and R2.
Ryan Dahl on Twitter / X
Introducing celld: a self-hosted, distributed Durable Objects and Workers implementation- celld = V8 + S3 + SQLite + LTX+ Tokio- programmed with exactly the Cloudflare Workers/DO JavaScript APIs and config- order of magnitude cheaper at scale- writes are durable before… pic.twitter.com/KCBf6U5DQw— Ryan Dahl (@rough__sea) August 5, 2026
Comment on: Permissioned Data Diary 2: Buckets - Daniel&#...
"a bucket doesn’t necessarily imply a physical container sitting on one PDS. Consider how threads ..." The distributed-vs-centralized storage question is where this gets really interesting. If buc...
Wildland (@WildlandIO) on X
An open protocol for data management that allows users to have sole ownership of their data. Join us! https://t.co/AqwplMcG9u Developed by @GolemFoundation
Permissioned Data Diary 2: Buckets - Daniel's Leaflets
The second in a series of posts building up a solution to permissioned data on atproto. We introduce buckets: a new protocol primitive for creating a shared social context.
AWS re:Invent 2018: Amazon DynamoDB Under the Hood: How We Built a Hyper-Scale Database (DAT321)
Permissioned Data Diary 3: Your Bucket, My Data - Daniel's Leaflets
The third in a series of posts building up a solution to permissioned data on atproto. We look at two different models for where buckets live and why the simpler-looking one doesn’t work out.
Overview · vlpds docs
An atproto PDS whose only durable storage is an object store. Any node serves any request, one node can run a personal server for free, and a few nodes can carry all of Bluesky's write load.
An introduction to Conflict-Free Replicated Data Types (CRDTs)
SingleStore launched cloud business after third attempt
: Apache Iceberg support makes it a good option for a transactional layer over data lakes, he tells The Register
Understanding new Cloud Storage hierarchical namespace | Google Cloud Blog
The new hierarchical namespace capabilities bring file system optimizations to Cloud Storage buckets.
Willow - Home
Peer-to-peer protocols which scale up, down, and sideways. Sychronisable data storage, fine-grained access control, private and efficient synchronisation, and secure data delivery by any means possible.
Conflict-Free Replicated Data Types
Replicating data under Eventual Consistency (EC) allows any replica to accept updates without remote synchronisation. This ensures performance and scalability in large-scale distributed systems (e.g., clouds). However, published EC approaches are ad-hoc and error-prone. Under a formal Strong Eventual Consistency (SEC) model, we study sufficient conditions for convergence. A data type that satisfies these conditions is called a Conflict-free Replicated Data Type (CRDT). Replicas of any CRDT are guaranteed to converge in a self-stabilising manner, despite any number of failures. This paper formalises two popular approaches (state- and operation-based) and their relevant sufficient conditions. We study a number of useful CRDTs, such as sets with clean semantics, supporting both add and remove operations, and consider in depth the more complex Graph data type. CRDT types can be composed to develop large-scale distributed applications, and have interesting theoretical properties.
DuckLake Architecture Deep Dive
DuckLake is a next generation data lakehouse and open table format. It is significantly simpler and faster than Apache Iceberg or Delta Lake because it uses a SQL database for storing the catalog and metadata. This post covers an architecture deep dive with a detailed Q&A section. DuckLake consists of 3 components: storage, catalog, and compute. Each can be scaled independently, hosted locally with ease, and deployed to the cloud for production. MotherDuck offers managed DuckLake lakehouses for additional simplicity and performance.
continuing to build up our permissioned data protocol! this one asks what a bucket actually is and where the data that constitutes a bucket is stored. it argues for maintaining the atproto ethos in the permissioned data protocol as always, looking forward to hearing your thoughts!
Permissioned Data Diary 3: Your Bucket, My Data
dholms.leaflet.pub