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Based on our record, DBeaver should be more popular than Apache Parquet. It has been mentiond 93 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.
The Apache Spark / Databricks community prefers Apache parquet or Linux Fundation's delta.io over json. Source: 5 months ago
Apache Parquet (Parquet for short), which nowadays is an industry standard to store columnar data on disk. It compress the data with high efficiency and provides fast read and write speeds. As written in the Arrow documentation, "Arrow is an ideal in-memory transport layer for data that is being read or written with Parquet files". - Source: dev.to / 12 months ago
Googling that suggests this page: https://parquet.apache.org/. Source: about 1 year ago
You should also consider distribution of data because in a company that has machine learning workflows, the same data may need to go through different workflows using different technologies and stored in something other than a data warehouse, e.g. Feature engineering in Spark and loaded/stored in binary format such as Parquet in a data lake/object store. Source: about 1 year ago
This section will teach you how to read and write data to and from a variety of file types, including CSV, Excel, SQL, HTML, Parquet, JSON etc. You’ll also learn how to manipulate data from other sources, such as databases and web sites. Source: about 1 year ago
It’s cool to show a demo and talk about the infrastructure with cute diagrams, but I always want to prove, even if just to myself, that things work as expected. So I thought a good way to test it would be to try connecting directly to both databases using my database client, DBeaver. - Source: dev.to / about 2 months ago
List of db clients I have bookmarked https://dbeaver.io/. - Source: Hacker News / about 2 months ago
As a great alternative to DBeaver, DBGate provides a variety of tools to manage your databases. Besides in built-in support charts and a query builder, you can use Javascript to query data. It even supports NoSQL drivers and native script builders. Give it a try if your project demands simplicity over in-depth features for SQL databases. - Source: dev.to / 4 months ago
This isn’t meant to be an exhaustive list. There are many other database management software packages out there, including MySQL Workbench, DBeaver, and pgAdmin. We’ve chosen these database tools because they cover the most common database systems and use cases, but if you find they aren’t meeting your needs, be sure to explore further or consider building your own database user interface — it’s easier than you... - Source: dev.to / 4 months ago
Tools like TablePlus, DBeaver, or HeidiSQL provide visual query building interfaces. While not performance analysis tools per se, they can help you build and understand complex queries more easily. - Source: dev.to / 7 months ago
Apache Arrow - Apache Arrow is a cross-language development platform for in-memory data.
DataGrip - Tool for SQL and databases
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
MySQL Workbench - MySQL Workbench is a unified visual tool for database architects, developers, and DBAs.
Apache ORC - Apache ORC is a columnar storage for Hadoop workloads.
HeidiSQL - HeidiSQL is a powerful and easy client for MySQL, MariaDB, Microsoft SQL Server and PostgreSQL. Open source and entirely free to use.