Data PostgreSQL SQL Structured Data 
Rockset
NOVEMBER 5, 2021
Summary: DataBrain, a SaaS company, was using PostgreSQL through Amazon RDS to land and query incoming customer data. However, PostgreSQL couldn’t scale, quickly ingest schemaless data, or efficiently run analytics as DataBrain’s data grew. One customer was already generating 60 million rows of data.
Rockset
JULY 9, 2019
One of the main hindrances to getting value from our data is that we have to get data into a form that’s ready for analysis. Consider the hoops we have to jump through when working with semi-structured data, like JSON, in relational databases such as PostgreSQL and MySQL. Other data types require more thought.
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ProjectPro
FEBRUARY 16, 2023
The demand for skilled data engineers who can build, maintain, and optimize large data infrastructures does not seem to slow down any sooner. At the heart of these data engineering skills lies SQL that helps data engineers manage and manipulate large amounts of data. of data engineer job postings on Indeed?
Rockset
JULY 6, 2022
This is the fifth post in a series by Rockset's CTO and Co-founder Dhruba Borthakur on Designing the Next Generation of Data Systems for Real-Time Analytics. So are schemaless NoSQL databases, which capably ingest firehoses of data but are poor at extracting complex insights from that data. SQL queries were easier to write.
Knowledge Hut
MARCH 27, 2024
On the other hand, data structures are like the tools that help organize and arrange data within a computer program. In simpler terms, a database is where information is neatly stored, like books on shelves, while data structures are the behind-the-scenes helpers, ensuring data is well-organized and easy to find.
Cloudera
JUNE 3, 2022
Data scientists and machine learning engineers in enterprise organizations need to fully understand their data in order to properly analyze it, build models, and power machine learning use cases across their business. Data scientists are likely to use a variety of different tools to move through their processes.
Data Engineering Podcast
AUGUST 31, 2020
Summary Data warehouse technology has been around for decades and has gone through several generational shifts in that time. The current trends in data warehousing are oriented around cloud native architectures that take advantage of dynamic scaling and the separation of compute and storage.
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