AWS Big Data

OCTOBER 3, 2023

A data lake is a centralized repository that you can use to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights.

Data Lake 103

Data Lake Metadata Snapshot Recreation/Entertainment 103

AWS Big Data

MARCH 2, 2023

Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback. and later supports the Apache Iceberg framework for data lakes. The snapshot points to the manifest list. AWS Glue 3.0

Data Lake 119

Data Lake Data Processing Metadata Snapshot 119

Cloudera

FEBRUARY 14, 2024

Introduction Apache Iceberg has recently grown in popularity because it adds data warehouse-like capabilities to your data lake making it easier to analyze all your data — structured and unstructured. Problem with too many snapshots Everytime a write operation occurs on an Iceberg table, a new snapshot is created.

Strategy 59

Strategy Optimization Snapshot Metadata 59

AWS Big Data

MARCH 23, 2023

Register the S3 path storing the table using Lake Formation We register the S3 full path in Lake Formation: Navigate to the Lake Formation console. In the navigation pane, under Register and ingest , choose Data lake locations. For Data filter name , enter blog_data_filter. Choose Create new filter.

Interactive 70

Interactive Snapshot Data Lake Software 70

AWS Big Data

SEPTEMBER 13, 2023

A modern data architecture is an evolutionary architecture pattern designed to integrate a data lake, data warehouse, and purpose-built stores with a unified governance model. The company wanted the ability to continue processing operational data in the secondary Region in the rare event of primary Region failure.

Data Lake 92

Data Lake Data Processing Metadata Snapshot 92

AWS Big Data

APRIL 27, 2023

Amazon Athena supports the MERGE command on Apache Iceberg tables, which allows you to perform inserts, updates, and deletes in your data lake at scale using familiar SQL statements that are compliant with ACID (Atomic, Consistent, Isolated, Durable).

Data Lake 75

Data Lake Snapshot Optimization Data Transformation 75

Cloudera

FEBRUARY 8, 2024

Subsequently, these snapshot IDs are used to determine the delta changes that should be applied to the materialized view rows. Incremental and full rebuild of materialized view We will insert rows into the base table and examine how the materialized view can be updated to reflect the new data.

Snapshot 94

Snapshot Metadata Cost-Benefit Data Warehouse 94