Altexsoft

MARCH 31, 2020

It means you must collect transactional data and move it from the database that supports transactions to another system that can handle large volumes of data. And, as is common, to transform it before loading to another storage system. But how do you move data? The simplest illustration for a data pipeline.

Data 76

Data Storage Analytics Data Center 76

Cloudera

MAY 13, 2021

Since my last blog, What you need to know to begin your journey to CDP , we received many requests for a tool from Cloudera to analyze the workloads and help upgrade or migrate to Cloudera Data Platform (CDP). Fixed Reports / Data Engineering jobs . Fixed Reports / Data Engineering Jobs. Report Format.

Data Engineering 74

Data Engineering Cloud Weak Development Team Resources 74

Cloudera

SEPTEMBER 14, 2020

Everybody needs more data and more analytics, with so many different and sometimes often conflicting needs. Data engineers need batch resources, while data scientists need to quickly onboard ephemeral users. The post Fundamentals for Success in Cloud Data Management appeared first on Cloudera Blog.

Cloud 111

Cloud Data Compliance Government 111

Cloudera

AUGUST 30, 2022

Agencies are plagued by a wide range of data formats and storage environments—legacy systems, databases, on-premises applications, citizen access portals, innumerable sensors and devices, and more—that all contribute to a siloed ecosystem and the data management challenge. . That’s just the tip of the iceberg.

Architecture 82

Architecture Data Artificial Inteligence Artificial Intelligence 82

Cloudera

APRIL 22, 2021

Today’s enterprise data analytics teams are constantly looking to get the best out of their platforms. Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it. Supports Disaggregation of compute and storage.

Data 103

Data Storage Architecture Big Data 103

Cloudera

AUGUST 24, 2020

In the last blog with Deloitte’s Marc Beierschoder, we talked about what the hybrid cloud is, why it can benefit a business and what the key blockers often are in implementation. The most relevant use cases are those that use or integrate data, including publicly available data, and you combine that with your internal data.

Cloud 82

Cloud Data Government Innovation 82

Cloudera

AUGUST 20, 2021

The Cloudera Data Platform comprises a number of ‘data experiences’ each delivering a distinct analytical capability using one or more purposely-built Apache open source projects such as Apache Spark for Data Engineering and Apache HBase for Operational Database workloads.

Strategy 100

Strategy Data Technical Review Weak Development Team 100

Altexsoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. A topic, in turn, is divided into partitions — the smallest units of storage space, hosting an ordered sequence of messages. A single cluster can span across multiple data centers and cloud facilities.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Cloudera

DECEMBER 12, 2018

For example, Impala uses the Hive metastore catalog as its data dictionary and it operates directly on data existing in HDFS, which is found through the Namenode API. So, they have the same components: a catalog, query compilation, query execution, and file management and storage, yet they’re independent of each other.

Data 42

Data Marketing Storage Big Data 42

Kentik

NOVEMBER 16, 2015

Here at Kentik, our Kentik Detect service is powered by a multi-tenant big data datastore called Kentik Data Engine. KDE handles — on a daily basis — tens of billions of network flow records, ingestion of several TB of data, and many millions of sub-queries. Workers are processes that run on our storage nodes.

Metrics 40

Metrics Microservices Linux Architecture 40

Cloudera

FEBRUARY 14, 2022

When we introduced Cloudera Data Engineering (CDE) in the Public Cloud in 2020 it was a culmination of many years of working alongside companies as they deployed Apache Spark based ETL workloads at scale. It’s no longer driven by data volumes, but containerization, separation of storage and compute, and democratization of analytics.

Data Engineering 116

Data Engineering Engineering Data Storage 116

Cloudera

JANUARY 11, 2021

Cloudera Data Warehouse (CDW) is a cloud service and an integral part of the newly released Cloudera Data Platform (CDP). Key features are: Highly scalable and performant open-source engines for BI and data warehousing workloads. Separate compute from storage. Data can be served to the business with ease.

Data 64

Data Pharmaceuticals Open Source Machine Learning 64

Cloudera

OCTOBER 13, 2021

These companies have instead opted to leverage their existing data centre investment. Turning the data center into a private cloud would bring all the agility and flexibility of public cloud to the control of an on-premises infrastructure. Move to more Data Services. Next stop: hybrid data cloud.

Data Center 101

Data Center Cloud Data How To 101

Cloudera

MAY 18, 2021

Second, since IaaS deployments replicated the on-premises HDFS storage model, they resulted in the same data replication overhead in the cloud (typical 3x), something that could have mostly been avoided by leveraging modern object store. Storage costs. using list pricing of $0.72/hour hour using a r5d.4xlarge

Cloud 86

Cloud Technical Review Storage Backup 86