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. 2 – Use a Data Virtualization Tool The next approach is to use a data virtualization tool.

MongoDB 52

MongoDB NoSQL Data Warehouse BI 52

Rockset

OCTOBER 4, 2022

Streaming data feeds many real-time analytics applications, from logistics tracking to real-time personalization. Event streams, such as clickstreams, IoT data and other time series data, are common sources of data into these apps. ClickHouse has several storage engines that can pre-aggregate data.

MySQL 52

MySQL Kafka Aggregated Data Architecture 52

AltexSoft

OCTOBER 21, 2022

This enables systems using Kafka to aggregate data from many sources and to make it consistent. Instead of interfering with each other, Kafka consumers create groups and split data among themselves. Hadoop fits heavy, not time-critical analytics applications that generate insights for long-term planning and strategic decisions.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93