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Handling Out-of-Order Data in Real-Time Analytics Applications

Rockset

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).

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Five Ways to Run Analytics on MongoDB – Their Pros and Cons

Rockset

MongoDB is a top database choice for application development. Developers choose this database because of its flexible data model and its inherent scalability as a NoSQL database. MongoDB wasn’t originally developed with an eye on high performance for analytics. The downsides of data warehouses are data and query latency.

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The Good and the Bad of Apache Kafka Streaming Platform

AltexSoft

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. cloud data warehouses — for example, Snowflake , Google BigQuery, and Amazon Redshift. You can find off-the-shelf links for.

Kafka 93