Cloudera

JULY 26, 2021

Auditabily: Data security and compliance constituents need to understand how data changes, where it originates from and how data consumers interact with it. To that end, encryption at rest and in motion across the data landscape need to be enforced in a comprehensive and systematic manner. .

Generalist 119

Generalist Telecommunication Healthcare Data 119

Netflix Tech

OCTOBER 27, 2020

For example, in order to enhance our user experience, one online application fetches subscribers’ preferences data to recommend movies and TV shows. The data warehouse is not designed to serve point requests from microservices with low latency.

Data Warehouse 97

Data Warehouse Datasets Data Big Data 97

Netflix Tech

DECEMBER 14, 2018

data access semantics that guarantee repeatable data read behavior for client applications. The following section enumerates the key traits of NMDB and how the design aims to address them. key value stores generally allow storing any data under a key). However unlike the media data schema, MID schema is immutable.

Media 94

Media Database Metadata Data Schemas 94

Confluent

JUNE 13, 2019

The LSST is expected to detect about 10 million transient objects each night, an order of magnitude more than ZTF, with a nightly data stream size of 1–2 TB of messages. There were a number of factors we considered in designing an alert distribution for ZTF. Alert data pipeline and system design.

Kafka 102

Kafka Bytes Data Pipeline Python 102

ProjectPro

JANUARY 31, 2023

Data Storage: The next step after data ingestion is to store it in HDFS or a NoSQL database such as HBase. HBase storage is ideal for random read/write operations, whereas HDFS is designed for sequential processes. Data Processing: This is the final step in deploying a big data model. RDBMS stores structured data.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Netflix Tech

OCTOBER 31, 2018

The curious reader might have noticed that a majority of these characteristics relate to properties of the data managed by NMDB. Specifically, structured data that is modeled around the notion of a media timeline, with additional spatial properties. Hence, we designed it primarily around the notion of timed events.

Media 54

Media Metadata Data MongoDB 54

ProjectPro

APRIL 26, 2016

Pig vs Hive Criteria Pig Hive Type of Data Apache Pig is usually used for semi structured data. Used for Structured Data Schema Schema is optional. Hive requires a well-defined Schema. Language It is a procedural data flow language. Follows SQL Dialect and is a declarative language.

Hadoop 40

Hadoop Metadata SQL Database 40