Why SQL is beating NoSQL, and what this means for the future of data

Why SQL is beating NoSQL, and what this means for the future of data

9/26/2017

link

https://blog.timescale.com/why-sql-beating-nosql-what-this-means-for-future-of-data-time-series-database-348b777b847a/

summary

This blog post discusses the advantages of using SQL (Structured Query Language) over NoSQL (Not only SQL) for managing data, particularly in the context of time-series databases. The author highlights the scalability, flexibility, and robustness of SQL databases compared to NoSQL alternatives. They argue that SQL's declarative nature allows for easier data manipulation and querying, making it more suitable for complex data analysis tasks. The post also emphasizes the importance of standardization and compatibility, suggesting that SQL's widespread adoption and ecosystem contribute to its superiority. Overall, the author predicts a promising future for SQL databases in handling time-series data.

tags

data organization ꞏ nosql ꞏ data durability ꞏ data indexing ꞏ data exploration ꞏ data integrity ꞏ sql vs nosql ꞏ data migration ꞏ data mining ꞏ data security ꞏ data insights ꞏ data recovery ꞏ data reliability ꞏ data scalability ꞏ data trends ꞏ data querying language ꞏ data-driven decision-making ꞏ time series databases ꞏ data replication ꞏ data schemas ꞏ data performance ꞏ data warehousing ꞏ database architecture ꞏ data volatility ꞏ data processing ꞏ data science ꞏ data backup ꞏ data consistency ꞏ data storage ꞏ database technology ꞏ data structures ꞏ data serialization ꞏ data querying ꞏ data engineering ꞏ data evolution ꞏ data modeling ꞏ data manipulation ꞏ data analysis ꞏ data governance ꞏ data visualization ꞏ sql ꞏ database design ꞏ data optimization ꞏ data retrieval ꞏ data management ꞏ data analytics