Project
Apache Iceberg is an open-source table format for large analytic datasets, letting multiple engines query and manage huge tables on object storage.
Amazon S3, S3 Tables and S3 Vectors can now be created from the Vercel Marketplace and v0, with no AWS console step for policies or credentials. Functions trade short-lived OIDC tokens with AWS STS, so no static keys sit in the project.
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Iceberg 1.11.0 ships a File Format API that sends Spark, Flink, Hive and plain-Java reads and writes through one registry of format models. A dev.to walkthrough says the file format list stays fixed, so Vortex and Lance still need a change inside Iceberg.
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RustFS embeds an Apache-2.0 Iceberg REST catalog in its object store and serves it on the S3 port, according to a dev.to walkthrough. Teams can drop a separate metastore, but catalog metadata then shares a failure domain with the data.
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Databricks opened a public Beta of a Unity Catalog connector that queries Workday HR and finance data in place, without copying it. The company's own guidance keeps history-tracked reporting on its separate Lakeflow Connect ingestion path.
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Amazon Web Services added Iceberg materialized views to Redshift, so a result Redshift computes once can be read by Spark and Athena, a dev.to write-up says. Teams that copy shared metrics between engines with ETL jobs can retire those jobs only if the views stay fresh enough for their readers.
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Salesforce Data 360 instruments about eight million Spark runs a day at one submission gateway, without changing application code. The plugin fails open, so a broken collector leaves the platform team a data gap to chase while customer jobs keep running.
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A dev.to walkthrough found DuckDB's operator names in the EXPLAIN output of AWS's aurora_analytics extension, on a Parquet query that executed in 81 ms. That run hit a warm cache on one 500,000-row file, so it tells you which engine ran far more than how fast it will be on lake-scale data.
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Databricks says it added UNREGISTER to the Apache Iceberg REST catalog spec, so a table can change catalogs with zero files copied. A team can only use it if the catalog it is leaving implements the call, and the post demonstrates it on Unity Catalog.
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Cloudflare made its Data Platform generally available as Basin, three serverless services that ingest, catalog and query Apache Iceberg tables on R2. Outside Iceberg engines read the same tables, so Workers teams can price Basin SQL against a warehouse on identical data.
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AWS has embedded DuckDB in Aurora PostgreSQL from versions 17.11 and 18.6, so one SQL query can join live rows with Iceberg and Parquet tables in S3. Reverse-ETL jobs that exist only for that join can be retired if the database instance has room for the lake scans.
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Apache Iceberg's REST Catalog spec now lets a catalog return per-user row filters and nine column actions for a trusted engine to enforce, Databricks says. Policies that need subqueries or lookup tables do not fit that vocabulary, so the portability covers simple rules running on engines a deployment already trusts.
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Amazon S3 Tables now supports every Apache Iceberg V3 data type after adding four, including geometry, geography and nanosecond timestamps. Telemetry and mapping teams can stop storing event times and coordinates as integers and strings.
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AWS Community Builder Aki argues Apache Iceberg made data portable while permissions, auditing, lineage and sharing stay tied to each catalog. The spec leaves the atomic commit to each catalog, so the catalog is now the choice that is hard to reverse.
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Rust's Iceberg REST client ran up to 4.29x faster than pyiceberg on a local catalog, with 85% to 90% of the gap in Python's HTTP library. pyiceberg covers 21 of 25 tested endpoints to Rust's 13, so coverage settles the choice before speed does.
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Apache Iceberg's Rust REST client, iceberg-catalog-rest 0.10.1, implements 13 of 25 tested catalog operations and logs in to five of seven catalogs. The two it cannot log in to are AWS Glue and S3 Tables, and reaching them from Rust means a different crate with a different operation set.
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Reviewers logged 10,991 passing tests on Iceberg's first 1.12.0 candidate before rejecting it over two vendored web files. The change most likely to break a downstream build is a removed partition-statistics helper.
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Keeping the Iceberg table format governance-unaware was a deliberate call. That leaves the catalog as the only thing standing on the path of every read. A dev.to guide lists six pieces an operator has to source above it.
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A runnable two-agent example moves every refusal into the catalog that vends credentials, because a key covers a storage prefix and there are no rows at the point of enforcement. The author works on that catalog.
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A dev.to post argues that Snowflake-managed Iceberg tables let you keep the managed engine while owning the Parquet in your own bucket. The same post says the catalog stays Snowflake's, and that 50,000-inserts-per-second ingest should not move.
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AWS has published a pipeline that pulls Bedrock guardrail traces out of model invocation logs, rewrites them as OCSF Detection Findings, and lands them in the CloudWatch store where analysts already query CloudTrail and VPC Flow Logs.
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Build · August 26, 2026 · Confirmed2 publishers