#apacheiceberg — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #apacheiceberg, aggregated by home.social.
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Next Wednesday: the engineer who built ColdFront live on the architecture.
Most #Postgres databases pay SSD prices for data nobody queries. ColdFront gives you #PostgreSQL to #ApacheIceberg using the same #SQL and the same table names with writable cold tier.
On August 19, 8 AM PST, catch @vyruss on the engineering + TLA+-verified distributed writes. Paul Rothrock will give a live demo.
Q&A at the end.
📅 https://us02web.zoom.us/webinar/register/WN_3oRFbue0QL2UI7j9DmCbFA
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Next Wednesday: the engineer who built ColdFront live on the architecture.
Most #Postgres databases pay SSD prices for data nobody queries. ColdFront gives you #PostgreSQL to #ApacheIceberg using the same #SQL and the same table names with writable cold tier.
On August 19, 8 AM PST, catch @vyruss on the engineering + TLA+-verified distributed writes. Paul Rothrock will give a live demo.
Q&A at the end.
📅 https://us02web.zoom.us/webinar/register/WN_3oRFbue0QL2UI7j9DmCbFA
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Open source transparent #Postgres tiering to Apache Iceberg. Same table names, same SQL, OLTP + analytics + AI in one database. Cold data is still writable - one DELETE handles a GDPR request, no restore-to-hot cycle.
In-process #DuckDB (no sidecar, no daemon). Stock upstream #PostgreSQL. Up to 90% cheaper storage. @vyruss (who built it) + Paul Rothrock live demo - August 19, 8 AM PST.
🔗 https://github.com/pgEdge/ColdFront
📅 https://us02web.zoom.us/webinar/register/WN_3oRFbue0QL2UI7j9DmCbFA -
Open source transparent #Postgres tiering to Apache Iceberg. Same table names, same SQL, OLTP + analytics + AI in one database. Cold data is still writable - one DELETE handles a GDPR request, no restore-to-hot cycle.
In-process #DuckDB (no sidecar, no daemon). Stock upstream #PostgreSQL. Up to 90% cheaper storage. @vyruss (who built it) + Paul Rothrock live demo - August 19, 8 AM PST.
🔗 https://github.com/pgEdge/ColdFront
📅 https://us02web.zoom.us/webinar/register/WN_3oRFbue0QL2UI7j9DmCbFA -
Most Postgres databases store 80-90% of their rows on expensive SSD that nobody's queried in months.
ColdFront is pgEdge's open source answer: moves cold data to Apache Iceberg on object storage (up to 90% cheaper) while keeping the same table names, SQL, and connection string. No application changes. No vendor lock-in.
Jimmy Angelakos (who built it) & Paul Rothrock demo it live - 8/19, 8 AM PST. Register: 📅 https://hubs.la/Q04rdpHQ0
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Most Postgres databases store 80-90% of their rows on expensive SSD that nobody's queried in months.
ColdFront is pgEdge's open source answer: moves cold data to Apache Iceberg on object storage (up to 90% cheaper) while keeping the same table names, SQL, and connection string. No application changes. No vendor lock-in.
Jimmy Angelakos (who built it) & Paul Rothrock demo it live - 8/19, 8 AM PST. Register: 📅 https://hubs.la/Q04rdpHQ0
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Learn about Cloudflare's Town Lake, its unified internal data platform, where billing workloads account for 53% of all platform queries.
Built alongside Skipper, an AI-powered analytics agent, Town Lake unifies access to operational, billing, security, and business data that was previously spread across fragmented systems.
Details here ➤ https://bit.ly/4bvWOGR
#Cloudflare #ApacheIceberg #Postgres #DataAnalytics #DataPlatform #DataGovernance #PlatformEngineering #InfoQ
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Learn about Cloudflare's Town Lake, its unified internal data platform, where billing workloads account for 53% of all platform queries.
Built alongside Skipper, an AI-powered analytics agent, Town Lake unifies access to operational, billing, security, and business data that was previously spread across fragmented systems.
Details here ➤ https://bit.ly/4bvWOGR
#Cloudflare #ApacheIceberg #Postgres #DataAnalytics #DataPlatform #DataGovernance #PlatformEngineering #InfoQ
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In most tiering systems, cold data is read-only. A GDPR deletion on archived rows means restore-delete-rearchive: a half-day job.
ColdFront: UPDATE or DELETE archived rows with one SQL statement.
HFS Research analyst Ashish Chaturvedi, in Anirban Ghoshal's InfoWorld piece today. ColdFront appears alongside Databricks, Snowflake & EDB on the OLTP/OLAP divide. The only 100% #OpenSource option, with #Postgres as the interface. -
In most tiering systems, cold data is read-only. A GDPR deletion on archived rows means restore-delete-rearchive: a half-day job.
ColdFront: UPDATE or DELETE archived rows with one SQL statement.
HFS Research analyst Ashish Chaturvedi, in Anirban Ghoshal's InfoWorld piece today. ColdFront appears alongside Databricks, Snowflake & EDB on the OLTP/OLAP divide. The only 100% #OpenSource option, with #Postgres as the interface. -
Cold data is read-only - that's the assumption baked into basically every tiering solution on the market. ColdFront breaks it.
UPDATE & DELETE on archived rows work through standard SQL. A GDPR deletion on five-year-old events is a single DELETE statement. No restore cycle.
DuckDB in-process, Apache Iceberg on any S3. Stock unpatched #PostgreSQL 16/17/18. Beta now, PostgreSQL License. Led by Jimmy Angelakos.
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Cold data is read-only - that's the assumption baked into basically every tiering solution on the market. ColdFront breaks it.
UPDATE & DELETE on archived rows work through standard SQL. A GDPR deletion on five-year-old events is a single DELETE statement. No restore cycle.
DuckDB in-process, Apache Iceberg on any S3. Stock unpatched #PostgreSQL 16/17/18. Beta now, PostgreSQL License. Led by Jimmy Angelakos.
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pgEdge ColdFront: #PostgreSQL data tiering. Hot data in the heap, cold to Apache Iceberg on S3 - up to 90% lower storage cost.
The cold tier is writable. UPDATE & DELETE on cold rows work in standard SQL. No restore cycle, no rehydration. No app changes.
DuckDB runs in-process. No daemon, no sidecar. PostgreSQL License, beta now. Led by @vyruss.
Press release: 👉 https://www.pgedge.com/press-releases/pgedge-announces-coldfront-for-postgresql
GitHub: 🔗 https://github.com/pgEdge/coldfront
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pgEdge ColdFront: #PostgreSQL data tiering. Hot data in the heap, cold to Apache Iceberg on S3 - up to 90% lower storage cost.
The cold tier is writable. UPDATE & DELETE on cold rows work in standard SQL. No restore cycle, no rehydration. No app changes.
DuckDB runs in-process. No daemon, no sidecar. PostgreSQL License, beta now. Led by @vyruss.
Press release: 👉 https://www.pgedge.com/press-releases/pgedge-announces-coldfront-for-postgresql
GitHub: 🔗 https://github.com/pgEdge/coldfront
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I'lll spare you the "I did a thing" cliché and just say I'm really proud to share what I've been building lately: #pgEdge ColdFront is live.
Figuring out how to move #PostgreSQL data to #S3 while keeping it queryable and updatable as if it were still local, without requiring any application code changes, is exactly the kind of hard problem I enjoy.
Check out the link below to see how it all works under the hood.
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I'lll spare you the "I did a thing" cliché and just say I'm really proud to share what I've been building lately: #pgEdge ColdFront is live.
Figuring out how to move #PostgreSQL data to #S3 while keeping it queryable and updatable as if it were still local, without requiring any application code changes, is exactly the kind of hard problem I enjoy.
Check out the link below to see how it all works under the hood.
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🧊 pgEdge ColdFront beta is out - transparent data tiering for #PostgreSQL. Fully writable cold tier.
Hot data stays in the heap. Cold data moves to Iceberg on S3 at up to 90% lower cost. UPDATE & DELETE on archived rows, same SQL. No rehydration. No code changes.
DuckDB runs in-process - no daemon, no RPC. C extension routes DML to the correct tier transparently.
Development by Jimmy Angelakos. Blog by Antony Pegg: 📖 https://www.pgedge.com/blog/introducing-coldfront-seamlessly-uniting-oltp-analytics-and-ai-workloads-on-postgresql
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🧊 pgEdge ColdFront beta is out - transparent data tiering for #PostgreSQL. Fully writable cold tier.
Hot data stays in the heap. Cold data moves to Iceberg on S3 at up to 90% lower cost. UPDATE & DELETE on archived rows, same SQL. No rehydration. No code changes.
DuckDB runs in-process - no daemon, no RPC. C extension routes DML to the correct tier transparently.
Development by Jimmy Angelakos. Blog by Antony Pegg: 📖 https://www.pgedge.com/blog/introducing-coldfront-seamlessly-uniting-oltp-analytics-and-ai-workloads-on-postgresql
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DuckDB Labs released #DuckLake 1.0 - a data lake format that stores table metadata in a SQL database, rather than spreading it across object storage files.
Key features:
• catalog-stored small updates
• improved sorting and partitioning
• compatibility with Iceberg-style data featuresLearn more ⇨ https://bit.ly/48PsPIS
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DuckDB Labs released #DuckLake 1.0 - a data lake format that stores table metadata in a SQL database, rather than spreading it across object storage files.
Key features:
• catalog-stored small updates
• improved sorting and partitioning
• compatibility with Iceberg-style data featuresLearn more ⇨ https://bit.ly/48PsPIS
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Lakehouse architectures allow multiple engines to run on shared data through open table formats like #ApacheIceberg.
But #SQL identifier resolution and catalog naming rules differ across engines - creating hidden interoperability failures.
In this #InfoQ article, Maninder Parmar explains why enforcing consistent naming conventions and cross-engine validation is critical.
📰 Read now: https://bit.ly/4902zeH
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Lakehouse architectures allow multiple engines to run on shared data through open table formats like #ApacheIceberg.
But #SQL identifier resolution and catalog naming rules differ across engines - creating hidden interoperability failures.
In this #InfoQ article, Maninder Parmar explains why enforcing consistent naming conventions and cross-engine validation is critical.
📰 Read now: https://bit.ly/4902zeH
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The Data Lakehouse Explained: Why Apache Iceberg Is Quietly Running the Show
https://techlife.blog/posts/data-lakehouse-iceberg
#ApacheIceberg #DataLakehouse #DataWarehouse #DataLake #Snowflake #ApacheSpark #DataEngineering
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#Pinterest launched a next-gen CDC-based ingestion framework.
Using #ApacheKafka, #ApacheFlink, #ApacheSpark & #ApacheIceberg, they achieved:
• Latency cut from 24+ hours to 15 minutes
• Processing of only changed records
• Support for incremental updates & deletions
• Petabyte-scale data across 1,000+ pipelinesWin: optimized cost & efficiency!
Read the architectural deep dive on InfoQ 👉 https://bit.ly/4rMJB2H
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#Pinterest launched a next-gen CDC-based ingestion framework.
Using #ApacheKafka, #ApacheFlink, #ApacheSpark & #ApacheIceberg, they achieved:
• Latency cut from 24+ hours to 15 minutes
• Processing of only changed records
• Support for incremental updates & deletions
• Petabyte-scale data across 1,000+ pipelinesWin: optimized cost & efficiency!
Read the architectural deep dive on InfoQ 👉 https://bit.ly/4rMJB2H
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#AWS announced 2 new capabilities for #S3Tables!
🔹 Intelligent-Tiering storage class that automatically optimizes costs based on access patterns
🔹 Replication support that keeps Apache Iceberg table replicas consistent across AWS regions and accounts - no manual syncing requiredFind out more: https://bit.ly/4qgRn3Y
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#AWS announced 2 new capabilities for #S3Tables!
🔹 Intelligent-Tiering storage class that automatically optimizes costs based on access patterns
🔹 Replication support that keeps Apache Iceberg table replicas consistent across AWS regions and accounts - no manual syncing requiredFind out more: https://bit.ly/4qgRn3Y
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Преодоление разрыва между озерами данных и хранилищами данных
Системы хранения данных типа «озера данных» сочетают в себе гибкость озер данных с надежностью, производительностью и возможностями управления, характерными для хранилищ данных.
В современных аналитических системах компании в значительной степени полагаются на озера данных...
#DST #DSTGlobal #ДСТ #ДСТГлобал #озёраданных #хранилищаданных #lakehouse #ApacheIceberg #Метаданные #Кэширование
Источник: https://dstglobal.ru/club/1144-preodolenie-razryva-mezhdu-ozerami-dannyh-i-hranilischami-dannyh
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#DuckDB now supports end-to-end interaction with Iceberg REST Catalogs directly in the browser - no infrastructure setup required.
With DuckDB-Wasm, users can query, read, and write Iceberg tables seamlessly.
Learn more: https://bit.ly/4qCTYoF
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#DuckDB now supports end-to-end interaction with Iceberg REST Catalogs directly in the browser - no infrastructure setup required.
With DuckDB-Wasm, users can query, read, and write Iceberg tables seamlessly.
Learn more: https://bit.ly/4qCTYoF
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Cloudflare has just launched the open beta of its Cloudflare Data Platform - a managed service for ingesting, storing & querying analytical data tables using open standards like Apache Iceberg.
🔍 Dive into the key insights on #InfoQ ⇨ https://bit.ly/49y1tIa
#CloudComputing #DataLake #DataAnalytics #ApacheIceberg #Cloudflare
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Cloudflare has just launched the open beta of its Cloudflare Data Platform - a managed service for ingesting, storing & querying analytical data tables using open standards like Apache Iceberg.
🔍 Dive into the key insights on #InfoQ ⇨ https://bit.ly/49y1tIa
#CloudComputing #DataLake #DataAnalytics #ApacheIceberg #Cloudflare
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scrapy-contrib-bigexporter 0.6.1 released: https://codeberg.org/ZuInnoTe/scrapy-contrib-bigexporters
Added: You can customize Iceberg table location
#scrapy #webscraping #bigdata #iceberg #apacheiceberg #opensource #python
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scrapy-contrib-bigexporter 0.6.1 released: https://codeberg.org/ZuInnoTe/scrapy-contrib-bigexporters
Added: You can customize Iceberg table location
#scrapy #webscraping #bigdata #iceberg #apacheiceberg #opensource #python
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scrapy-contrib-bigexporter 0.6.0 released: https://codeberg.org/ZuInnoTe/scrapy-contrib-bigexporters
New: Export your webscraped items in Scrapy to Apache Iceberg tables with simple configuration
#scrapy #webscraping #bigdata #iceberg #apacheiceberg #opensource #python
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scrapy-contrib-bigexporter 0.6.0 released: https://codeberg.org/ZuInnoTe/scrapy-contrib-bigexporters
New: Export your webscraped items in Scrapy to Apache Iceberg tables with simple configuration
#scrapy #webscraping #bigdata #iceberg #apacheiceberg #opensource #python
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#Netflix scaled 𝐌𝐮𝐬𝐞 to handle 𝐭𝐫𝐢𝐥𝐥𝐢𝐨𝐧-𝐫𝐨𝐰 𝐝𝐚𝐭𝐚𝐬𝐞𝐭𝐬!
➡️ Muse helps teams see which artwork & videos resonate with audiences.
➡️ To keep up with demand, Netflix 𝐫𝐞𝐝𝐞𝐬𝐢𝐠𝐧𝐞𝐝 𝐭𝐡𝐞 𝐝𝐚𝐭𝐚 𝐥𝐚𝐲𝐞𝐫, cutting query latencies by ~50% while keeping results accurate and responsive.🔗 Learn more: https://bit.ly/4gG3HGU
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#Netflix scaled 𝐌𝐮𝐬𝐞 to handle 𝐭𝐫𝐢𝐥𝐥𝐢𝐨𝐧-𝐫𝐨𝐰 𝐝𝐚𝐭𝐚𝐬𝐞𝐭𝐬!
➡️ Muse helps teams see which artwork & videos resonate with audiences.
➡️ To keep up with demand, Netflix 𝐫𝐞𝐝𝐞𝐬𝐢𝐠𝐧𝐞𝐝 𝐭𝐡𝐞 𝐝𝐚𝐭𝐚 𝐥𝐚𝐲𝐞𝐫, cutting query latencies by ~50% while keeping results accurate and responsive.🔗 Learn more: https://bit.ly/4gG3HGU
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Watching the re-indexing of an archival catalog backup of AtoM, I realized:
Indices populated with 18751 documents in 164.84 seconds.
19k Objects?
Thats /nothing/ for a regular #bigDATA tech-tool. This is peanuts.400.000 Objects?
Millions?! - According to documentation of #ApacheIceberg #ObjectStore #Redis #KeyDB, etc: **easy**#DLTP & #GLAM: Storing and using those "objects" in key/value annotated filesystems with bigDATA tools:
**FUN!!**
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Amazon #S3 now supports sort and z-order compaction for #ApacheIceberg tables, promising reduced scan times & lower engine costs.
Available for both S3 Tables and traditional S3 buckets via AWS Glue Data Catalog optimization.
Dive into the details: https://bit.ly/3GyjxWQ
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Amazon #S3 now supports sort and z-order compaction for #ApacheIceberg tables, promising reduced scan times & lower engine costs.
Available for both S3 Tables and traditional S3 buckets via AWS Glue Data Catalog optimization.
Dive into the details: https://bit.ly/3GyjxWQ
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📢 Behold, the earth-shattering breakthrough of Nimtable: a web UI to *click* on Apache Iceberg tables! 🙄 Presumably because using command line tools is an insurmountable task for mere mortals. Or maybe it’s just a clever way to make clicking around a web interface the new rocket science. 🚀
https://github.com/nimtable/nimtable #Nimtable #ApacheIceberg #WebUI #Innovation #TechNews #ClickAndGo #HackerNews #ngated -
📢 Behold, the earth-shattering breakthrough of Nimtable: a web UI to *click* on Apache Iceberg tables! 🙄 Presumably because using command line tools is an insurmountable task for mere mortals. Or maybe it’s just a clever way to make clicking around a web interface the new rocket science. 🚀
https://github.com/nimtable/nimtable #Nimtable #ApacheIceberg #WebUI #Innovation #TechNews #ClickAndGo #HackerNews #ngated -
Nimtable: Open-source web UI to browse and manage Apache Iceberg tables
https://github.com/nimtable/nimtable
#HackerNews #Nimtable #OpenSource #ApacheIceberg #WebUI #DataManagement #DatabaseTools
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Nimtable: Open-source web UI to browse and manage Apache Iceberg tables
https://github.com/nimtable/nimtable
#HackerNews #Nimtable #OpenSource #ApacheIceberg #WebUI #DataManagement #DatabaseTools
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Paris: Apache Iceberg Paris Community Meetup #1, Le jeudi 19 juin 2025 de 18h00 à 21h30. https://www.agendadulibre.org/events/32653 #data #dataLakehouse #dataEngineer #dataScience #dataPlatform #dataWarehouse #apacheIceberg
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Paris: Apache Iceberg Paris Community Meetup #1, Le jeudi 19 juin 2025 de 18h00 à 21h30. https://www.agendadulibre.org/events/32653 #data #dataLakehouse #dataEngineer #dataScience #dataPlatform #dataWarehouse #apacheIceberg
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"Centralize Your Data Lake: Apache Polaris Supports Apache Iceberg and Now Delta Lake"
BTW 'Polaris' used to be the name of the UK nuclear deterrent pre 1996. 😬
https://snowflake.com/en/engineering-blog/apache-polaris-supports-iceberg-delta-lake/
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"Centralize Your Data Lake: Apache Polaris Supports Apache Iceberg and Now Delta Lake"
BTW 'Polaris' used to be the name of the UK nuclear deterrent pre 1996. 😬
https://snowflake.com/en/engineering-blog/apache-polaris-supports-iceberg-delta-lake/
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What happens when you marry #ClickHouse database with #ApacheIceberg? you could query huge datasets fast and with 10x cheaper storage. Sounds promising, right?
Join me tomorrow on the live stream to find out!
May 20th, 11am PT / 20:00 CET:
https://www.youtube.com/watch?v=VeyTL2JlWp0 -
What happens when you marry #ClickHouse database with #ApacheIceberg? you could query huge datasets fast and with 10x cheaper storage. Sounds promising, right?
Join me tomorrow on the live stream to find out!
May 20th, 11am PT / 20:00 CET:
https://www.youtube.com/watch?v=VeyTL2JlWp0