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Data Storage Formats for Big Data Analytics: Performance and Cost Implications of Parquet, Avro, and ORC

DZone

Efficient data processing is crucial for businesses and organizations that rely on big data analytics to make informed decisions. One key factor that significantly affects the performance of data processing is the storage format of the data.

Big Data 278
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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

High performance, query optimization, open source and polymorphic data storage are the major Greenplum advantages. When handling large amounts of complex data, or big data, chances are that your main machine might start getting crushed by all of the data it has to process in order to produce your analytics results.

Big Data 321
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Introduction to Azure Data Lake Storage Gen2

DZone

Built on Azure Blob Storage, Azure Data Lake Storage Gen2 is a suite of features for big data analytics. Azure Data Lake Storage Gen1 and Azure Blob Storage's capabilities are combined in Data Lake Storage Gen2.

Azure 250
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Cutting Big Data Costs: Effective Data Processing With Apache Spark

DZone

Spark takes full advantage of this storage property by exclusively reading the columns that are involved in subsequent computations.

Big Data 279
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In-Stream Big Data Processing

Highly Scalable

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. The pipelines can be stateful and the engine’s middleware should provide a persistent storage to enable state checkpointing. Towards Unified Big Data Processing.

Big Data 154
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Optimizing data warehouse storage

The Netflix TechBlog

At this scale, we can gain a significant amount of performance and cost benefits by optimizing the storage layout (records, objects, partitions) as the data lands into our warehouse. We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits.

Storage 225
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Apache Doris vs Elasticsearch: An In-Depth Comparative Analysis

DZone

In the field of big data analytics, Apache Doris and Elasticsearch (ES) are frequently utilized for real-time analytics and retrieval tasks. It comprises front-end and back-end components, leveraging multi-node parallel computing and columnar storage to efficiently manage massive datasets.

Analytics 130