JSON VS Amazon Redshift

JSON Reviews

Amazon Redshift Reviews

JSON mentions (13)

• The Last Breaking Change | JSON Schema Blog

  The YAML 0.1 spec was sent to a public user group in May 2001. JSON was named in a State Software internal discussion. State Software was founded in March 2001. json.org was launched in 2002. Therefore you’re just wrong: YAML came out before JSON. Source: about 1 year ago

• Why does wine give warnings about using 64bit prefixes, or has 32bit packages? Hasn't the world moved on from 32 bit a century ago?

  How come that doesn't apply to other libraries? For example, when I write Java or Node.js programs, I don't need to make sure packages like json.org or express.js have a 32bit or 64bit environment. What makes windows libs different than NPM libs? Source: over 1 year ago

• “Ignore the f'ing haters ” And other lessons learned from creating a popular

  The first two sentences of the text on http://json.org are "JSON (JavaScript Object Notation) is a lightweight data-interchange format. It is easy for humans to read and write." It's a primary goal of JSON, it's fair to question whether it's successful at it. Personally, I'd much rather write TOML or S expressions. I don't like YAML at all, the whitespace sensitivity drives me nuts. - Source: Hacker News / almost 2 years ago

• Recording your JSON data to MCAP, a file format that support multiple serialization formats

  To help you make the transition, we’ve written a tutorial on how to write an MCAP writer in Python to record JSON data to an MCAP file. Source: almost 2 years ago

• replace \" with "

  What you need to probably do is to step back and learn the format for JSON, and the core data structures that you will find in most languages:. Source: almost 2 years ago

Amazon Redshift mentions (26)

• Choosing Between a Streaming Database and a Stream Processing Framework in Python

  They differ from conventional analytic databases like Snowflake, Redshift, BigQuery, and Oracle in several ways. Conventional databases are batch-oriented, loading data in defined windows like hourly, daily, weekly, and so on. While loading data, conventional databases lock the tables, making the newly loaded data unavailable until the batch load is fully completed. Streaming databases continuously receive new... - Source: dev.to / 3 months ago

• Choosing the Right AWS Database: A Guide for Modern Applications

  Data warehousing is the process of storing and analyzing large volumes of data for business intelligence and analytics purposes. AWS offers a fully managed data warehousing service called Amazon Redshift that can handle petabyte-scale data warehouses with ease. - Source: dev.to / 7 months ago

• A Comprehensive Guide to AWS DynamoDB vs. Redshift for Databases and Data Warehouses

  The topics of databases and data warehouses are central to the modern data landscape, and Amazon's offeringsDynamoDB and Redshiftare standout products in their respective categories. Here's a detailed comparison:. - Source: dev.to / 8 months ago

• AWS Redshift: Robust and Scalable Data Warehousing

  Amazon Redshift is a powerful, scalable data warehousing service within the AWS ecosystem. It excels in handling large datasets with its columnar storage, parallel query execution, and features like Redshift Spectrum and RA3 instances. Redshift’s clustered architecture, robust security, and integration with AWS services make it a go-to choice for businesses needing efficient and secure data management solutions. - Source: dev.to / 11 months ago

• AWS Beginner's Key Terminologies

  Amazon Redshift (analytics) Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. With Amazon Redshift, you can analyze your data using your existing business intelligence tools. Https://aws.amazon.com/redshift/. - Source: dev.to / over 1 year ago