Azure Databricks is a service available on Microsoft's Azure platform and suite of products. It provides the latest versions of Apache Spark so users can integrate with open source libraries, or spin up clusters and build in a fully managed Apache Spark environment with the global scale and availability of Azure. Clusters are set up, configured, and fine-tuned to ensure reliability and performance without the need for monitoring. The solution includes autoscaling and auto-termination to improve…
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PostgreSQL
Score 8.8 out of 10
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PostgreSQL (alternately Postgres) is a free and open source object-relational database system boasting over 30 years of active development, reliability, feature robustness, and performance. It supports SQL and is designed to support various workloads flexibly.
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Pricing
Azure Databricks
PostgreSQL
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Azure Databricks
PostgreSQL
Free Trial
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Free/Freemium Version
No
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Premium Consulting/Integration Services
No
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Entry-level Setup Fee
No setup fee
No setup fee
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Community Pulse
Azure Databricks
PostgreSQL
Features
Azure Databricks
PostgreSQL
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Azure Databricks
8.1
2 Ratings
3% below category average
PostgreSQL
-
Ratings
Connect to Multiple Data Sources
6.42 Ratings
00 Ratings
Extend Existing Data Sources
9.02 Ratings
00 Ratings
Automatic Data Format Detection
9.12 Ratings
00 Ratings
MDM Integration
8.01 Ratings
00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Azure Databricks
6.2
2 Ratings
30% below category average
PostgreSQL
-
Ratings
Visualization
5.82 Ratings
00 Ratings
Interactive Data Analysis
6.72 Ratings
00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Azure Databricks
8.1
2 Ratings
0% below category average
PostgreSQL
-
Ratings
Interactive Data Cleaning and Enrichment
7.02 Ratings
00 Ratings
Data Transformations
8.92 Ratings
00 Ratings
Data Encryption
9.12 Ratings
00 Ratings
Built-in Processors
7.22 Ratings
00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Azure Databricks
8.3
2 Ratings
1% below category average
PostgreSQL
-
Ratings
Multiple Model Development Languages and Tools
8.22 Ratings
00 Ratings
Automated Machine Learning
8.92 Ratings
00 Ratings
Single platform for multiple model development
8.12 Ratings
00 Ratings
Self-Service Model Delivery
8.12 Ratings
00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Suppose you have multiple data sources and you want to bring the data into one place, transform it and make it into a data model. Azure Databricks is a perfectly suited solution for this. Leverage spark JDBC or any external cloud based tool (ADG, AWS Glue) to bring the data into a cloud storage. From there, Azure Databricks can handle everything. The data can be ingested by Azure Databricks into a 3 Layer architecture based on the delta lake tables. The first layer, raw layer, has the raw as is data from source. The enrich layer, acts as the cleaning and filtering layer to clean the data at an individual table level. The gold layer, is the final layer responsible for a data model. This acts as the serving layer for BI For BI needs, if you need simple dashboards, you can leverage Azure Databricks BI to create them with a simple click! For complex dashboards, just like any sql db, you can hook it with a simple JDBC string to any external BI tool.
PostgreSQL is best used for structured data, and best when following relational database design principles. I would not use PostgreSQL for large unstructured data such as video, images, sound files, xml documents, web-pages, especially if these files have their own highly variable, internal structure.
Based on my extensive use of Azure Databricks for the past 3.5 years, it has evolved into a beautiful amalgamation of all the data domains and needs. From a data analyst, to a data engineer, to a data scientist, it jas got them all! Being language agnostic and focused on easy to use UI based control, it is a dream to use for every Data related personnel across all experience levels!
Postgresql is the best tool out there for relational data so I have to give it a high rating when it comes to analytics, data availability and consistency, so on and so forth. SQL is also a relatively consistent language so when it comes to building new tables and loading data in from the OLTP database, there are enough tools where we can perform ETL on a scalable basis.
The data queries are relatively quick for a small to medium sized table. With complex joins, and a wide and deep table however, the performance of the query has room for improvement.
There are several companies that you can contract for technical support, like EnterpriseDB or Percona, both first level in expertise and commitment to the software.
But we do not have contracts with them, we have done all the way from googling to forums, and never have a problem that we cannot resolve or pass around. And for dozens of projects and more than 15 years now.
The online training is request based. Had there been recorded videos available online for potential users to benefit from, I could have rated it higher. The online documentation however is very helpful. The online documentation PDF is downloadable and allows users to pace their own learning. With examples and code snippets, the documentation is great starting point.
Against all the tools I have used, Azure Databricks is by far the most superior of them all! Why, you ask? The UI is modern, the features are never ending and they keep adding new features. And to quote Apple, "It just works!" Far ahead of the competition, the delta lakehouse platform also fares better than it counterparts of Iceberg implementation or a loosely bound Delta Lake implementation of Synapse
Although the competition between the different databases is increasingly aggressive in the sense that they provide many improvements, new functionalities, compatibility with complementary components or environments, in some cases it requires that it be followed within the same family of applications that performs the company that develops it and that is not all bad, but being able to adapt or configure different programs, applications or other environments developed by third parties apart is what gives PostgreSQL a certain advantage and this diversification in the components that can be joined with it, is the reason why it is a great option to choose.
Easy to administer so our DevOps team has only ever used minimal time to setup, tune, and maintain.
Easy to interface with so our Engineering team has only ever used minimal time to query or modify the database. Getting the data is straightforward, what we do with it is the bigger concern.