TEteleforce·Nov 5, 2025Submission
1 points · Open discussiondelta-io
delta
Scala2019–2025
delta-io / delta
delta
An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
9Distinct people
11Mentions
0Explicit recommenders
9.1KGitHub stars
What to know before exploring
What it is
An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
GitHub
Where it is used
No documented product use has been verified yet.
What people are saying
No recommendation phrase was found in the indexed comments.
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Also in these discussions
No other repository is repeatedly linked in the same discussions.
This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by year11 dated mentions
Observed mentions: 2019-04-24 18:42:21 UTC to 2025-11-05 09:32:45 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2019 | 2019-01-01 00:00:00 UTC | 2020-01-01 00:00:00 UTC | 2 | 2 | 0 |
| 2020 | 2020-01-01 00:00:00 UTC | 2021-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2021 | 2021-01-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 2 | 0 | 2 |
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 2 | 1 | 1 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 4 | 1 | 3 |
What Hacker News says
11 sourcesOK, but at least from my perspective, the point of OTF’s is to allow ongoing interoperability between query and update engines.
A “standard” getting semi-monthly updates via random Databricks-affiliated GitHub accounts doesn’t really fit that bill.
Look at something like this:
https://github.com/delta-io/delta/blob/master/PROTOCOL.md#wr...
Ouch.
In Apache Iceberg V3 Spec new features for more efficient and flexible data lakesThe Iceberg spec is a model of clarity and simplicity compared to the (constantly in flux via Databricks commits…) Delta protocol spec:
https://github.com/delta-io/delta/blob/master/PROTOCOL.md
In Apache Iceberg V3 Spec new features for more efficient and flexible data lakesHidden partitioning is the most interesting Iceberg feature, because most of the very large datasets are timeseries fact tables.
I don't remember seeing that in Delta Lake [1], which is probably because the industry standard benchmarks use date as a column (tpc-h) or join date as a dimension table (tpc-ds) and do not use timestamp ranges instead of dates.
[1] - https://github.com/delta-io/delta/issues/490
In Apache IcebergI often hear references to Apache Iceberg and Delta Lake as if they’re two peas in the Open Table Formats pod. Yet…
Here’s the Apache Iceberg table format specification:
https://iceberg.apache.org/spec/
As they like to say in patent law, anyone “skilled in the art” of database systems could use this to build and query Iceberg tables without too much difficulty.
This is nominally the Delta Lake equivalent:
https://github.com/delta-io/delta/blob/master/PROTOCOL.md
I defy anyone to even scope out what level of effort would be required to fully implement the current spec, let alone what would be involved in keeping up to date as this beast evolves.
Frankly, the Delta Lake spec reads like a reverse engineering of whatever implementation tradeoffs Databricks is making as they race to build out a lakehouse for every Fortune 1000 company burned b
Read the rest
y Hadoop (which is to say, most of them).
My point is that I’ve yet to be convinced that buying into Delta Lake is actually buying into an open ecosystem. Would appreciate any reassurance on this front!
Editing to append this GitHub history, which is unfortunately not reassuring:
https://github.com/delta-io/delta/commits/master/PROTOCOL.md
Random features and tweaks just popping up, PR’d by Databricks engineers and promptly approved by Databricks senior engineers…
https://delta.io/blog/2022-05-05-delta-lake-1-2-released/ - big part is open sourced and more is coming (see roadmap on GitHub: https://github.com/delta-io/delta/issues/920)
In The end of big data>the delta also still keeps partitioning information in the hive metastore, while iceberg keeps it in storage, making it a far superior design.
Check out https://github.com/delta-io/delta/blob/3ffb30d86c6acda9b59b9... when you get a chance. You don't need hive metastore to query delta tables since all metadata for a Delta table is stored alongside the data
>they did not include features like optimizing small files
For optimizing small files, you could run https://docs.delta.io/latest/best-practices.html#compact-fil...
In Snowflake’s response to Databricks’ TPC-DS postthis is the right url: https://github.com/delta-io/delta
In Databricks is an RDBMSDatabricks Open Sources Delta Lake
1 points · Open discussion