article thumbnail

Designing A Non-Relational Database Engine

Data Engineering Podcast

The default association with the term "database" is relational engines, but non-relational engines are also used quite widely. In this episode Oren Eini, CEO and creator of RavenDB, explores the nuances of relational vs. non-relational engines, and the strategies for designing a non-relational database.

article thumbnail

MongoDB vs DynamoDB Head-to-Head: Which Should You Choose?

Rockset

Editor Databases are a key architectural component of many applications and services. Traditionally, organizations have chosen relational databases like SQL Server, Oracle , MySQL and Postgres. Relational databases use tables and structured languages to store data.

MongoDB 52
Insiders

Sign Up for our Newsletter

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

article thumbnail

Methods for Running SQL on JSON in PostgreSQL, MySQL and Other Relational Databases

Rockset

Consider the hoops we have to jump through when working with semi-structured data, like JSON, in relational databases such as PostgreSQL and MySQL. JSON is a good match for document databases, such as MongoDB. Now, consider what we have to do to load JSON data into a relational database.

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.

MongoDB 52
article thumbnail

Extracting MongoDB fields - even nested ones

Grouparoo

If you’re a data analyst, data scientist, developer, or DB administrator you may have used, at some point, a non-relational database with flexible schemas. Well, I could list several advantages of a NoSQL solution over SQL-based databases and vice versa.

MongoDB 52
article thumbnail

Handling Slow Queries in MongoDB - Part 2: Solutions

Rockset

In Part One , we discussed how to first identify slow queries on MongoDB using the database profiler, and then investigated what the strategies the database took doing during the execution of those queries to understand why our queries were taking the time and resources that they were taking.

MongoDB 40
article thumbnail

Big Data Technologies that Everyone Should Know in 2024

Knowledge Hut

There are a variety of big data processing technologies available, including Apache Hadoop, Apache Spark, and MongoDB. Spark also supports SQL queries and machine learning algorithms. NoSQL databases are designed for scalability and flexibility, making them well-suited for storing big data. HDFS, Cassandra, Hive).