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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Google Cloud AI
Score 8.7 out of 10
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Google Cloud AI provides modern machine learning services, with pre-trained models and a service to generate tailored models.
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Pricing
Azure Databricks
Google Cloud AI
Editions & Modules
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Pricing Offerings
Azure Databricks
Google Cloud AI
Free Trial
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No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Azure Databricks
Google Cloud AI
Features
Azure Databricks
Google Cloud AI
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Azure Databricks
8.1
Ratings
3% below category average
Google Cloud AI
-
Ratings
Connect to Multiple Data Sources
6.20 Ratings
00 Ratings
Extend Existing Data Sources
9.00 Ratings
00 Ratings
Automatic Data Format Detection
9.00 Ratings
00 Ratings
MDM Integration
8.00 Ratings
00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Azure Databricks
6.4
Ratings
27% below category average
Google Cloud AI
-
Ratings
Visualization
5.90 Ratings
00 Ratings
Interactive Data Analysis
6.90 Ratings
00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Azure Databricks
8.0
Ratings
2% below category average
Google Cloud AI
-
Ratings
Interactive Data Cleaning and Enrichment
7.00 Ratings
00 Ratings
Data Transformations
9.00 Ratings
00 Ratings
Data Encryption
9.00 Ratings
00 Ratings
Built-in Processors
7.10 Ratings
00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Azure Databricks
8.3
Ratings
1% below category average
Google Cloud AI
-
Ratings
Multiple Model Development Languages and Tools
8.10 Ratings
00 Ratings
Automated Machine Learning
9.00 Ratings
00 Ratings
Single platform for multiple model development
8.00 Ratings
00 Ratings
Self-Service Model Delivery
8.00 Ratings
00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Having access to all databases and tables in one place is what has helped me and my team to function better. The in built functionality/access to SQL and Python is definitely an added bonus! The icing on the cake is the ability to export your data into an Excel spreadsheet for additional analysis. If you have less to no working knowledge of SQL or Python, its better to look at alternatives.
Google Images analysis model is a good one and I think is very useful in our case of detections. Speech AI is also a good one. I can only recommend Google Cloud AI API and the model for that second will be SpeechKit by Yandex both these tools have exceptional values one can utilise to enhance their projects.
Smart reply and its AI suggestions make the organization think more carefully about their e-mail responses in Gmail. We were skeptical at first but it really works well for many instances.
We do a lot of business and contracts in Western Europe and South America, so the translate solutions make this much easier for our banking paperwork.
When we go to meetings or during a meeting, we often use the Google voice search to save time on research and filtering ideas or analysis.
Hard to find what to use - To find the right products, you need look closely at the details of each API, and find which suits your purposes. This can be easily fixed by creating a main page that details all of the products simply.
Expensive - The API costs can quickly add up, especially during the setup process and as engineers figure out the usage of the API.
No playground or training - There is a lack of an "API playground" or training sessions that could make onboarding engineers to this API much easier.
We are extremely satisfied with the impact that this tool has made on our organization since we have practically moved from crawling to walking in the process of generating information for our main task to investigate in the field through interviews. With the audio to text translation tool there is a difference from heaven to earth in the time of feeding our internal data.
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!
I give 8 because although it´s a tool I really enjoy working with, I think Google Cloud AI's impact is just starting, therefore I can visualize a lot/space of improvements in this tool. As an example the application of AI in international environments with different languages is a good example of that space/room to improve.
Every rep has been nice and helpful whenever I call for help. One of the systems froze and wouldn't start back up and with the help of our assigned rep we got everything back up in a timely manner. This helped us not lose customers and money.
In fact, you only need the basic tech knowledge to do a Google search. You need to know if your organization requires it or not,. our organization required it. And that is why we acquired it and solved a need that we had been suffering from. This is part of the modernization of an organization and part of its growth as a company.
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
Google's documentation for their AI and Machine Learning products is a bit more straightforward and still much easier to onboard into compared to the Azure Machine Learning and other AI products. Additionally, Google's Cloud AI products provide more comprehensive specific use-cases that are API-optimized, and easier to integrate into existing scripts and backends.