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Sebastian Galkin

@functionth.bsky.social

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Earthmover@earthmover.io · last yr.

𝐻𝑜𝑤 𝑑𝑜𝑒𝑠 𝐼𝑐𝑒𝑐ℎ𝑢𝑛𝑘 𝑎𝑣𝑜𝑖𝑑 𝑟𝑒𝑑𝑢𝑛𝑑𝑎𝑛𝑡 𝑠𝑡𝑜𝑟𝑎𝑔𝑒 𝑏𝑒𝑡𝑤𝑒𝑒𝑛 𝑑𝑎𝑡𝑎 𝑣𝑒𝑟𝑠𝑖𝑜𝑛𝑠? Icechunk stores only new or changed chunks for each version —no redundant copies or rewrites. You get instant time travel, branching, and efficient updates, all with negligible storage overhead. More: bit.ly/3F1XFST

Icechunk: Efficient storage of versioned array data - Earthmover

We recently got an interesting question in Icechunk’s community Slack channel (thank you Iury Simoes-Sousa for motivating this post): I’m new to Icechunk. How is the storage managed for redundant info...

earthmover.io

Earthmover@earthmover.io · last yr.

Our latest blog post dives into the chaos of the status quo - where every tweak means regenerating the 𝑤ℎ𝑜𝑙𝑒 𝑑𝑎𝑡𝑎𝑠𝑒𝑡 and collaboration and experimentation is often stifled by silos and secret knowledge. Check out the full post: earthmover.io/blog/tensoro...

TensorOps: Scientific Data Doesn't Have to Hurt - Earthmover

Curious how your team scores on the "Data Pain Survey"? Wondering why your teams are building Rube Goldberg machines just to put some data on a map? Or just want to see our plan to bring order to your...

earthmover.io

Sebastian Galkin@functionth.bsky.social · last yr.

Had the idea of using Icechunk (an multi-dimensional array database) for something I would never use Icechunk for

Earthmover@earthmover.io · last yr.

1/ 🚨 New Blog Post Alert: "𝐿𝑒𝑎𝑟𝑛𝑖𝑛𝑔 𝐴𝑏𝑜𝑢𝑡 𝐼𝑐𝑒𝑐ℎ𝑢𝑛𝑘 𝐶𝑜𝑛𝑠𝑖𝑠𝑡𝑒𝑛𝑐𝑦 𝑤𝑖𝑡ℎ 𝑎 𝐶𝑙𝑖𝑐ℎ𝑒́𝑑 𝑏𝑢𝑡 𝐼𝑛𝑠𝑡𝑟𝑢𝑐𝑡𝑖𝑣𝑒 𝐸𝑥𝑎𝑚𝑝𝑙𝑒" 🏦🔁 👉 Read it here: earthmover.io/blog/learnin...

Earthmover@earthmover.io · last yr.

📣 Blog post alert! 𝐄𝐱𝐩𝐥𝐨𝐫𝐢𝐧𝐠 𝐈𝐜𝐞𝐜𝐡𝐮𝐧𝐤 𝐬𝐜𝐚𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲: 𝐮𝐧𝐭𝐚𝐧𝐠𝐥𝐢𝐧𝐠 𝐒𝟑'𝐬 𝐩𝐫𝐞𝐟𝐢𝐱 𝐬𝐭𝐨𝐫𝐲. This technical post by @functionth.bsky.social dives deep into the internals of how S3 shards data, showing that distributed Icechunk can easily perform 230,000 object reads/sec and beyond. earthmover.io/blog/explori...

Exploring Icechunk scalability: untangling S3's prefix story | Earthmover

We show Icechunk can scale to extremely high concurrency levels, and explain how it achieves this in modern object stores.

earthmover.io

Joe Hamman@jhamman.bsky.social · last yr.

We often see folks try to convince tabular data tools to perform well with multi-dimensional array data. This post by @rabernat.bsky.social explains, from first principles, why this rarely works. Its a good one! 👇👇👇

Earthmover@earthmover.io · last yr.

⭐ We just released the first post in our Fundamentals series. This one is called 𝐓𝐞𝐧𝐬𝐨𝐫𝐬 𝐯𝐬. 𝐓𝐚𝐛𝐥𝐞𝐬 - 𝐖𝐡𝐲 𝐭𝐚𝐛𝐮𝐥𝐚𝐫 𝐭𝐨𝐨𝐥𝐬 𝐭𝐫𝐢𝐩 𝐨𝐯𝐞𝐫 𝐠𝐫𝐢𝐝𝐝𝐞𝐝 𝐝𝐚𝐭𝐚. earthmover.io/blog/tensors...

Sebastian Galkin@functionth.bsky.social · last yr.

I've worked on Icechunk almost exclusively for the last six months. I'm very proud of the result; you should check it out.

Earthmover@earthmover.io · last yr.

1/ 🚀 Solving #NASA ’s cloud data dilemma: Icechunk unlocks 100x faster access to archival data formats We're thrilled to publish results from our pilot project with NASA and @developmentseed.org to enable high-performance cloud-native access for NASA’s 100s of petabytes of Earth observation data.

Earthmover@earthmover.io · 2y ago

1/ Check out our latest blog post earthmover.io/blog/xarray-... to learn about the dramatic improvement and performance of Xarray’s Zarr backend. We achieved improved the “time to first byte” metric, building on Zarr-Python’s new asyncio internals.

Accelerating Xarray with Zarr-Python 3 | Earthmover

We have recently dramatically improved the performance of Xarray’s Zarr backend. This post explores how we’ve improved the “time to first byte” metric, building on Zarr-Python’s new asyncio internals.

earthmover.io