Cloudera

FEBRUARY 22, 2022

The data explosion has to be met with new solutions, that’s why we are excited to introduce the next generation table format for large scale analytic datasets within Cloudera Data Platform (CDP) – Apache Iceberg. Apache Iceberg is a new open table format targeted for petabyte-scale analytic datasets.

Metadata 109

Metadata Datasets BI SQL 109

Monte Carlo

NOVEMBER 14, 2023

Does it feel colder in here or is it all this Apache Iceberg talk? Databricks announced that Delta tables metadata will also be compatible with the Iceberg format, and Snowflake has also been moving aggressively to integrate with Iceberg. Table of Contents What is Apache Iceberg? Let’s dive in.

Data Lake 64

Data Lake Metadata Data Warehouse SQL 64

Cloudera

MARCH 23, 2022

Please join us on March 24 for Future of Data meetup where we do a deep dive into Iceberg with CDP . What is Apache Iceberg? Apache Iceberg is a high-performance, open table format, born-in-the cloud that scales to petabytes independent of the underlying storage layer and the access engine layer.

Metadata 92

Metadata Data Architecture BI Machine Learning 92

Cloudera

DECEMBER 15, 2022

Since we announced the general availability of Apache Iceberg in Cloudera Data Platform (CDP), Cloudera customers, such as Teranet , have built open lakehouses to future-proof their data platforms for all their analytical workloads. Cloudera partners are also benefiting from Apache Iceberg in CDP. Advanced capabilitie.

Cloud 80

Cloud Metadata Google Cloud Data Warehouse 80

Snowflake

MARCH 29, 2023

As announced at Snowflake Summit 2022 , Iceberg Tables combines unique Snowflake capabilities with Apache Iceberg and Apache Parquet open source projects to support your architecture of choice. What enables multiple, concurrent writers to run ACID transactions is a catalog. What is a catalog? What is a catalog?

Metadata 97

Metadata Scala Hadoop Relational Database 97

Cloudera

SEPTEMBER 9, 2022

Cloudera has been supporting data lakehouse use cases for many years now, using open source engines on open data and table formats, allowing for easy use of data engineering, data science, data warehousing, and machine learning on the same data, on premises, or in any cloud. An innovation in cloud-native table formats: Apache Iceberg.

Architecture 102

Architecture Metadata Unstructured Data Machine Learning 102

LinkedIn Engineering

JULY 19, 2023

Open source data lakehouse deployments are built on the foundations of compute engines (like Apache Spark, Trino, Apache Flink), distributed storage (HDFS, cloud blob stores), and metadata catalogs / table formats (like Apache Iceberg, Delta, Hudi, Apache Hive Metastore).

Big Data 78

Big Data Data Management Management Metadata 78