Based on our record, PostgreSQL should be more popular than Azure Synapse Analytics. It has been mentiond 16 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
In this quick post, we’ll walk through implementing an Upsert operation in Hasura using PostgreSQL and GraphQL. - Source: dev.to / 8 months ago
I’m on MacOS and erlang.org, elixir-lang.org, and postgresql.org all suggest installation via Homebrew, which is a very popular package manager for MacOS. - Source: dev.to / about 1 year ago
According to the documentation, crate sqlx is implemented in Rust, and it's database agnostic: it supports PostgreSQL, MySQL, SQLite, and MSSQL. - Source: dev.to / over 1 year ago
Solution is just downloading and installilng pgAdmin from official pgAdmin homepage version, not the one that is included in the postgresql.org package. Source: almost 2 years ago
SQL immediately stands out here because it was designed for making relational algebra, the other side of the Entity-Relationship model, accessible. There are likely more people who know SQL than any programming language (for IaC) or data format you could choose to represent your cloud infrastructure. Many non-programmers know it, as well, such as data scientists, business analysts, accountants, etc, and there is... - Source: dev.to / about 2 years ago
Azure Synapse Analytics: DbVisualizer now has extended support for dedicated and serverless SQL pools in Azure Synapse Analytics. That includes support for database-scoped credentials, external file formats and data sources, and external tables. For more information, see the Azure Synapse Dedicated and Azure Synapse Serverless pages on the official site. - Source: dev.to / 8 months ago
A data warehouse is a specialized database that's purpose built for gathering and analyzing data. Unlike general-purpose databases like MySQL or PostgreSQL, which are designed to meet the real-time performance and transactional needs of applications, a data warehouse is designed to collect and process the data produced by those applications, collectively and over time, to help you gain insight from it. Examples of... - Source: dev.to / over 2 years ago
You don't run into these kinds of problems with other tools, like the ones I mentioned. I've never tried the Azure ones, but my gut says they may have some scaling issues (synapse analytics looks promising but I have no experience with it). Source: about 3 years ago
Popular managed cloud data warehouse solutions include Azure Synapse Analytics, Azure SQL Database, and Amazon Redshift. - Source: dev.to / about 3 years ago
MySQL - The world's most popular open source database
Saturn Cloud - ML in the cloud. Loved by Data Scientists, Control for IT. Advance your business's ML capabilities through the entire experiment tracking lifecycle. Available on multiple clouds: AWS, Azure, GCP, and OCI.
Microsoft SQL - Microsoft SQL is a best in class relational database management software that facilitates the database server to provide you a primary function to store and retrieve data.
Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.
SQLite - SQLite Home Page
Google BigQuery - A fully managed data warehouse for large-scale data analytics.