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Amazon Redshift vs Microsoft Azure: What are the differences?
Scalability: Amazon Redshift and Microsoft Azure both offer scalability in terms of storage and compute resources. However, Amazon Redshift provides automatic scaling of both storage and compute, allowing users to easily add or remove nodes as needed. In contrast, Microsoft Azure provides manual scaling, requiring users to manually add or remove nodes to adjust the storage and compute capacity.
Pricing: When it comes to pricing, there are differences between Amazon Redshift and Microsoft Azure. Amazon Redshift offers a pay-as-you-go pricing model based on usage, with options for on-demand or reserved instances. On the other hand, Microsoft Azure offers a similar pay-as-you-go pricing model, but also provides options for purchasing reserved capacity to save costs in the long run.
Security and Compliance: Both Amazon Redshift and Microsoft Azure offer strong security features and compliance certifications. However, Amazon Redshift has more strict access control capabilities, allowing granular control over user permissions and access to data. Azure, on the other hand, offers strong security features and complies with various industry standards, but may require additional configuration for more granular access control.
Integration with Ecosystem: While Amazon Redshift is tightly integrated with the overall AWS ecosystem, including data ingestion, data lake storage, and various analytics services, Microsoft Azure provides a more comprehensive ecosystem with its own suite of data services, including Azure Data Lake Storage, Azure Data Factory, and Azure Analysis Services. This makes it easier for users who are already invested in the Azure ecosystem to work seamlessly with these services.
Data Warehousing Features: Amazon Redshift is specifically designed for data warehousing, offering a wide range of features optimized for performance, scalability, and analytical queries. On the other hand, Microsoft Azure offers a more diverse range of data services, including both data warehousing and database solutions. This allows users to choose the most appropriate solution based on their specific needs and requirements.
Geographical Availability: Amazon Redshift is available in multiple regions worldwide, allowing users to choose the location that best meets their needs for data residency and latency. Microsoft Azure also has a global presence, offering data warehousing services in several regions. However, the availability may vary across regions, and users should consider the available regions when selecting a provider.
In summary, Amazon Redshift and Microsoft Azure differ in terms of scalability, pricing models, security and compliance features, integration with ecosystem, data warehousing features, and geographical availability. Both platforms have their own strengths and users should evaluate these differences to choose the most suitable solution for their specific requirements.
We need to perform ETL from several databases into a data warehouse or data lake. We want to
- keep raw and transformed data available to users to draft their own queries efficiently
- give users the ability to give custom permissions and SSO
- move between open-source on-premises development and cloud-based production environments
We want to use inexpensive Amazon EC2 instances only on medium-sized data set 16GB to 32GB feeding into Tableau Server or PowerBI for reporting and data analysis purposes.
You could also use AWS Lambda and use Cloudwatch event schedule if you know when the function should be triggered. The benefit is that you could use any language and use the respective database client.
But if you orchestrate ETLs then it makes sense to use Apache Airflow. This requires Python knowledge.
Though we have always built something custom, Apache airflow (https://airflow.apache.org/) stood out as a key contender/alternative when it comes to open sources. On the commercial offering, Amazon Redshift combined with Amazon Kinesis (for complex manipulations) is great for BI, though Redshift as such is expensive.
You may want to look into a Data Virtualization product called Conduit. It connects to disparate data sources in AWS, on prem, Azure, GCP, and exposes them as a single unified Spark SQL view to PowerBI (direct query) or Tableau. Allows auto query and caching policies to enhance query speeds and experience. Has a GPU query engine and optimized Spark for fallback. Can be deployed on your AWS VM or on prem, scales up and out. Sounds like the ideal solution to your needs.
Pros of Amazon Redshift
- Data Warehousing41
- Scalable27
- SQL17
- Backed by Amazon14
- Encryption5
- Cheap and reliable1
- Isolation1
- Best Cloud DW Performance1
- Fast columnar storage1
Pros of Microsoft Azure
- Scales well and quite easy114
- Can use .Net or open source tools96
- Startup friendly81
- Startup plans via BizSpark73
- High performance62
- Wide choice of services38
- Low cost32
- Lots of integrations32
- Reliability31
- Twillio & Github are directly accessible19
- RESTful API13
- PaaS10
- Enterprise Grade10
- Startup support10
- DocumentDB8
- In person support7
- Free for students6
- Service Bus6
- Virtual Machines6
- Redis Cache5
- It rocks5
- Storage, Backup, and Recovery4
- Infrastructure Services4
- SQL Databases4
- CDN4
- Integration3
- Scheduler3
- Preview Portal3
- HDInsight3
- Built on Node.js3
- Big Data3
- BizSpark 60k Azure Benefit3
- IaaS3
- Backup2
- Open cloud2
- Web2
- SaaS2
- Big Compute2
- Mobile2
- Media2
- Dev-Test2
- Storage2
- StorSimple2
- Machine Learning2
- Stream Analytics2
- Data Factory2
- Event Hubs2
- Virtual Network2
- ExpressRoute2
- Traffic Manager2
- Media Services2
- BizTalk Services2
- Site Recovery2
- Active Directory2
- Multi-Factor Authentication2
- Visual Studio Online2
- Application Insights2
- Automation2
- Operational Insights2
- Key Vault2
- Infrastructure near your customers2
- Easy Deployment2
- Enterprise customer preferences1
- Documentation1
- Security1
- Best cloud platfrom1
- Easy and fast to start with1
- Remote Debugging1
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Cons of Amazon Redshift
Cons of Microsoft Azure
- Confusing UI7
- Expensive plesk on Azure2
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