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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. Yet, analytics is now a vital part of modern data applications.

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Performance Isolation for Your Primary MongoDB Cluster

Rockset

While MongoDB is often used as a primary online database and can meet the demands of very large scale web applications, it does often become the bottleneck as well. I had the opportunity to operate MongoDB at scale as a primary database at Foursquare, and encountered many of these bottlenecks.

MongoDB 40
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What is a Data Pipeline (and 7 Must-Have Features of Modern Data Pipelines)

Striim

Striim supported American Airlines by implementing a comprehensive data pipeline solution to modernize and accelerate operations. To achieve this, the TechOps team implemented a real-time data hub using MongoDB, Striim, Azure, and Databricks to maintain seamless, large-scale operations.

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14 Best Database Certifications in 2023 to Boost Your Career

Knowledge Hut

Skills acquired : Relational database concepts Retrieving data using the SQL SELECT statement. Sorting and restricting data. Using Conditional Expressions and Conversion functions Reporting Aggregated Data Using Group Functions Displaying data taken from multiple tables. MongoDB aggregation.

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Case Study: Is Your NoSQL Data Hindering Real-Time Analytics? Savvy Solved It with Rockset.

Rockset

We ended up deploying a real-time analytics platform, Rockset , on top of MongoDB. Rockset automatically ingests and prepares the data for any kind of query we might have already running or may need to throw at it. It feels like magic! The real-time performance was a huge boon, of course.

NoSQL 52
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How Rockset Enables SQL-Based Rollups for Streaming Data

Rockset

A Quick Primer on Indexing in Rockset Rockset allows users to connect real-time data sources — data streams (Kafka, Kinesis), OLTP databases (DynamoDB, MongoDB, MySQL, PostgreSQL) and also data lakes (S3, GCS) — using built-in connectors. You can also optionally use WHERE clauses to filter out data.

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Most important Data Engineering Concepts and Tools for Data Scientists

DareData

Examples of NoSQL databases include MongoDB or Cassandra. Data lakes: These are large-scale data storage systems that are designed to store and process large amounts of raw, unstructured data. Examples of technologies able to aggregate data in data lake format include Amazon S3 or Azure Data Lake.