U-Next

JUNE 27, 2023

Introduction Data analytics has been used as an efficient technique operating behind the scenes to manage the analytical job and get the best outcomes possible. While working with more complex data, Excel allows users to adjust the fields and functions that perform computations.

Utilities 52

Utilities Data Analysis Raw Data Aggregated Data 52

Rockset

FEBRUARY 2, 2022

Let’s explore five ways to run MongoDB analytics, along with the pros and cons of each method. 1 – Query MongoDB Directly The first and most direct approach is to run your analytical queries directly against MongoDB. The benefit of these tools is that they’re built specifically for data analytics.

MongoDB 52

MongoDB NoSQL Data Warehouse BI 52

Rockset

FEBRUARY 25, 2021

It’s difficult to create data analytics systems that can easily query across your various data sources while maintaining fast performance and real-time capabilities. Two of these real-time analytics solutions are Elasticsearch and Rockset. With the many data sources in today’s modern architecture, this can be difficult.

SQL 40

SQL Data Pipeline Kafka Database 40

AltexSoft

OCTOBER 21, 2022

In other words, Kafka can serve as a messaging system, commit log, data integration tool, and stream processing platform. The number of possible applications tends to grow due to the rise of IoT , Big Data analytics , streaming media, smart manufacturing, predictive maintenance , and other data-intensive technologies.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

Rockset

APRIL 15, 2022

Rockset not only continuously ingests data, but also can “rollup” the data as it is being generated. By using SQL to aggregate data as it is being ingested, this greatly reduces the amount of data stored (5-150x) as well as the amount of compute needed queries (boosting performance 30-100x).

Analytics Application 52

Analytics Application Data Warehouse Raw Data Kafka 52