Cloudera

APRIL 2, 2019

Apache HBase® is one of many analytics applications that benefit from the capabilities of Intel Optane DC persistent memory. HBase is a distributed, scalable NoSQL database that enterprises use to power applications that need random, real time read/write access to semi-structured data.

NoSQL 48

NoSQL Google Cloud Hadoop Machine Learning 48

Rockset

FEBRUARY 24, 2023

It has expanded to various industries and applications, including IoT sensor data, financial data, web analytics, gaming behavioral data, and many more use cases.

Kafka 52

Kafka AWS Amazon Web Services Programming Language 52

AltexSoft

JULY 18, 2023

It has in-memory computing capabilities to deliver speed, a generalized execution model to support various applications, and Java, Scala, Python, and R APIs. Spark Streaming enhances the core engine of Apache Spark by providing near-real-time processing capabilities, which are essential for developing streaming analytics applications.

Big Data 52

Big Data Data Process Process Hadoop 52

ProjectPro

MAY 20, 2015

The company targets to deliver values to its customers through the free SaaS based analytics applications so that it can build credibility with the clients to encourage them to buy more. Palantir Metropolis- This product focusses on information management, data integration and quantitative analytics.

Big Data 40

Big Data Hadoop Business Analyst Data Analytics 40

Rockset

FEBRUARY 25, 2021

For example, you might have to develop a real-time data pipeline using a tool like Kafka just to get the data in a format that allows you to aggregate or join data in a performant manner. Analyze Semi-Structured Data As Is The data feeding modern applications is rarely in neat little tables.

SQL 40

SQL Data Pipeline Kafka Database 40

ProjectPro

MARCH 15, 2016

They store and analyse massive volume of data from their manufactured mobile phones. To paint a fair picture of Nokia’s Big Data, they manage 100 TB of structured data along with 500+ TB of semi-structured data. Load a historical transactional point of sales data, into a Hadoop cluster.

Hadoop 40

Hadoop Retail Healthcare Banking 40

ProjectPro

FEBRUARY 16, 2023

To analyze big data and create data lakes and data warehouses , SQL-on-Hadoop engines run on top of distributed file systems. The SQL-on-Hadoop platform combines the Hadoop data architecture with traditional SQL-style structured data querying to create a specific analytical application tool.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

AltexSoft

SEPTEMBER 23, 2021

The result of experimentation supplies downstream applications with prepared data. A data hub serves as a gateway to dispense the required data. So the use of unstructured or semi-structured data is also available in a data hub, since a data lake can be a part of it.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

ProjectPro

JANUARY 31, 2023

Data Variety Hadoop stores structured, semi-structured and unstructured data. RDBMS stores structured data. Data storage Hadoop stores large data sets. RDBMS stores the average amount of data. Works with only structured data. The data may then be used in Apache Spark.

Big Data 52

Big Data Hadoop Relational Database AWS 52

phData: Data Engineering

JULY 18, 2023

CDWs are designed for running large and complex queries across vast amounts of data, making them ideal for centralizing an organization’s analytical data for the purpose of business intelligence and data analytics applications.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

ProjectPro

MAY 31, 2021

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications. Machines and humans are both sources of structured data.

Big Data 52

Big Data Coding Project Hadoop 52