Remove Events Remove Metadata Remove NoSQL Remove Structured Data
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Powering SQL Draw with Rockset, Retool and dbt

Rockset

As a key-value NoSQL database, storing and retrieving individual records are its bread and butter. For those unfamiliar, DynamoDB makes database scalability a breeze, but with some major caveats.

SQL 52
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Data Collection for Machine Learning: Steps, Methods, and Best Practices

AltexSoft

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. They can be accumulated in NoSQL databases like MongoDB or Cassandra.

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Data Lake vs Data Warehouse - Working Together in the Cloud

ProjectPro

This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data from data warehouses is queried using SQL.

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Hadoop vs Spark: Main Big Data Tools Explained

AltexSoft

HDFS master-slave structure. A HDFS Master Node, called a NameNode , keeps metadata with critical information about system files (like their names, locations, number of data blocks in the file, etc.) and keeps track of storage capacity, a volume of data being transferred, etc. Data storage options.

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Implementing the Netflix Media Database

Netflix Tech

A fundamental requirement for any lasting data system is that it should scale along with the growth of the business applications it wishes to serve. NMDB is built to be a highly scalable, multi-tenant, media metadata system that can serve a high volume of write/read throughput as well as support near real-time queries.

Media 94
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IBM InfoSphere vs Oracle Data Integrator vs Xplenty and Others: Data Integration Tools Compared

AltexSoft

Considered to be a leader in the field of data integration, Oracle Data Integrator (ODI) is a multi-functional solution that is part of Oracle’s data management ecosystem. The platform provides features for event-based , data-based, and service-based integration styles. Data profiling and cleansing.

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20 Best Open Source Big Data Projects to Contribute on GitHub

ProjectPro

It serves as a distributed processing engine for both categories of data streams: unbounded and bounded. Support for stream and batch processing, comprehensive state management, event-time processing semantics, and consistency guarantee for the state are just a few of Flink's capabilities.