article thumbnail

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.

MongoDB 52
article thumbnail

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.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Python for Data Engineering

Ascend.io

Use Case: Transforming monthly sales data to weekly averages import dask.dataframe as dd data = dd.read_csv('large_dataset.csv') mean_values = data.groupby('category').mean().compute() compute() Data Storage Python extends its mastery to data storage, boasting smooth integrations with both SQL and NoSQL databases.

article thumbnail

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.

SQL 52
article thumbnail

DynamoDB Filtering and Aggregation Queries Using SQL on Rockset

Rockset

Further, data is king, and users want to be able to slice and dice aggregated data as needed to find insights. Users don't want to wait for data engineers to provision new indexes or build new ETL chains. They want unfettered access to the freshest data available.

SQL 52
article thumbnail

100+ Data Engineer Interview Questions and Answers for 2023

ProjectPro

Non-relational databases are ideal if you need flexibility for storing the data since you cannot create documents without having a fixed schema. E.g. PostgreSQL, MySQL, Oracle, Microsoft SQL Server. E.g. Redis, MongoDB, Cassandra, HBase , Neo4j, CouchDB What is data modeling? How did you go about resolving this?