Cloudera

FEBRUARY 9, 2021

A typical approach that we have seen in customers’ environments is that ETL applications pull data with a frequency of minutes and land it into HDFS storage as an extra Hive table partition file. In this way, the analytic applications are able to turn the latest data into instant business insights. Low Maintenance.

Data Warehouse 71

Data Warehouse Cloud Kafka Cloud Storage 71

Rockset

MARCH 19, 2020

Intro In recent years, Kafka has become synonymous with “streaming,” and with features like Kafka Streams, KSQL, joins, and integrations into sinks like Elasticsearch and Druid, there are more ways than ever to build a real-time analytics application around streaming data in Kafka. To accomplish this we can use Kafka streams and KSQL.

Kafka 40

Kafka Database Process SQL 40

Cloudera

AUGUST 13, 2021

The business is so unprepared with information overflow that missing an important event or insight has become the business norm. The application license and infrastructure costs are rising faster than the ability to detect cyber events effectively. What product can help collect events only?

Data Pipeline 110

Data Pipeline Data Lake ETL Tools Unstructured Data 110

Cloudera

NOVEMBER 2, 2020

Ingest 100s of TB of network event data per day . The capabilities that more and more customers are asking for are: Analytics on live data AND recent data AND historical data. The capabilities that more and more customers are asking for are: Analytics on live data AND recent data AND historical data. 200,000 queries per day.

Data Warehouse 97

Data Warehouse Kafka Lambda Architecture Telecommunication 97

Rockset

MAY 3, 2023

In this blog, we’ll walk through the benchmark framework, configuration and results. We’ll also delve under the hood of the two databases to better understand why their performance differs when it comes to search and analytics on high-velocity data streams. Rockset achieved up to 4x higher throughput and 2.5x

Data Ingestion 59

Data Ingestion Kafka Database Architecture 59

AltexSoft

OCTOBER 21, 2022

This scenario involves three main characters — publishers, subscribers, and a message or event broker. A publisher (say, telematics or Internet of Medical Things system) produces data units, also called events or messages , and directs them not to consumers but to a middleware platform — a broker. Kafka cluster and brokers.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

Rockset

FEBRUARY 25, 2021

Often this lack of structure forces developers to spend a lot of their time engineering ETL and data pipelines so that analysts can access the complex datasets. Joins, in particular, are rarely well supported by alternative real-time analytics solutions. Instead, this data is often semi-structured in JSON or arrays.

SQL 40

SQL Data Pipeline Kafka Database 40

Cloudera

APRIL 2, 2019

When in memory mode, the data is not saved in the event of a power loss. In app direct mode, the application can utilize DRAM for operations that require low latency without persistency and leave Intel Optane DC persistent memory to handle large data structures at memory bus speeds without volatility.

NoSQL 48

NoSQL Google Cloud Hadoop Machine Learning 48

Cloudera

MAY 16, 2018

This approach also relates to monitoring internal fiduciary risk by tying separate events together, such as a large position (relative to historic norms) being taken immediately after the risk model that would have flagged it was modified in a separate system. The post Cross-Functional Trade Surveillance appeared first on Cloudera Blog.

Data Lake 42

Data Lake Electronics Media Unstructured Data 42

Cloudera

NOVEMBER 8, 2022

It enables cloud-native applications to store and process mass amounts of data in a hybrid multi-cloud environment and on premises. These could be traditional analytics applications like Spark, Impala, or Hive, or custom applications that access a cloud object store natively. Conclusion.

Metadata 85

Metadata Algorithm Hadoop Cloud 85

ProjectPro

MAY 23, 2015

Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Walmart was the world’s largest retailer in 2014 in terms of revenue. We want to know who every person in the world is. And we want to have the ability to connect them together in a transaction.”

Big Data 52

Big Data Data Analysis Hadoop Retail 52

Cloudera

JUNE 16, 2022

This blog aims to answer two questions as illustrated in the diagram below: How have stream processing requirements and use cases evolved as more organizations shift to “streaming first” architectures and attempt to build streaming analytics pipelines?

Kafka 89

Kafka Manufacturing Data Lake SQL 89

ProjectPro

MAY 31, 2021

This blog lists over 20 big data projects you can work on to showcase your big data skills and gain hands-on experience in big data tools and technologies. Here are some options for collecting data that you can utilize: Connect to an existing database that is already public or access your private database.

Big Data 52

Big Data Coding Project Hadoop 52

Rockset

APRIL 15, 2022

We'll be publishing more posts in the series in the near future, so subscribe to our blog so you don't miss them! So why are their analytics still crawling through in batches instead of real time? It’s probably because their analytics database lacks the features necessary to deliver data-driven decisions accurately in real time.

Analytics Application 52

Analytics Application Data Warehouse Raw Data Kafka 52