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Migrating from Heroku PostgreSQL to Snowflake: Top 3 Methods

Hevo

In today’s data-rich world, businesses must select the right data storage and analysis platform. For many, Heroku PostgreSQL has long been a trusted solution, offering a reliable relational database service in the cloud.

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How to query JSONB array of objects in PostgreSQL

Hevo

Do you have a NoSQL database that has no rigid shape and is causing data analysis complexity nightmares? With JSON in PostgreSQL, you can have a solution to your complex problem. PostgreSQL is a high-performing, open-sourced object-relational database with two JSON data storage types, JSON and JSONB.

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PostgreSQL on Google Cloud SQL to Snowflake: 2 Easy Methods to Load Data

Hevo

Google Cloud SQL for PostgreSQL, a part of Google’s robust cloud ecosystem, offers businesses a dependable solution for managing relational data. However, with the expanding need for advanced data analytics, it is required to integrate data storage and processing platforms like Snowflake.

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PostgreSQL on Amazon RDS to Firebolt Data Migration: 2 Easy Methods

Hevo

Migrating data between two platforms is a critical process for organizations to leverage the power of advanced analytics. The migration from PostgreSQL on Amazon RDS to Firebolt is one such example of how businesses can unlock the full potential of their data.

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Hive to PostgreSQL Integration: 2 Easy Methods to Connect

Hevo

Businesses need to efficiently store, handle, and analyze the growing amounts of data they produce. This article will explore the two prominent data storage systems organizations use: Hive and PostgreSQL.

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2 Easy Methods to Integrate Azure Postgres to BigQuery

Hevo

PostgreSQL, also known as Postgres, is an advanced object-relational database management system (ORDBMS) used for data storage, retrieval, and management. It is available on the Azure platform in a PaaS model (Platform as a Service) through the Azure Database for PostgreSQL service.

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ArangoDB: Fast, Scalable, and Multi-Model Data Storage with Jan Steeman and Jan Stücke - Episode 34

Data Engineering Podcast

How does the underlying engine store the data to allow for the different ways of viewing it? What are some of the benefits of multi-model data storage? For users who are accustomed to a relational engine, how do they need to adjust their approach to data modeling when working with Arango? How is ArangoDB constructed?