Azure Data Factory vs. Oracle Exadata

Best scenario is for ETL process. The flexibility and connectivity is outstanding. For our environment, SAP data connectivity with Azure Data Factory offers very limited features compared to SAP Data Sphere. Due to the limited modelling capacity of the tool, we use Databricks for data modelling and cleaning. Usage of multiple tools could have been avoided if adf has modelling capabilities.

Incentivized

Oracle Exadata is well-suited for environments where massive performance for Oracle databases is required. Storage indexes reduce the unnecessary I/O. Smart Flash
Cache accelerates random reads/writes.

Our OLTP application demands very high concurrency. Multi-node Exadata provides high availability and zero downtime during DB patching. It comes with lots of built-in automations, so it reduces many routine tasks for sysadmins, like network, storage, and VM configuration, and it also reduces many Oracle DBA tasks, like Oracle software installation, patching, and upgrades.

Incentivized

• Data Ingestion - it works very well with numerous data sources.
• Data pipeline orchestration: It is a generic, popular tool for orchestrating data pipelines.
• Works well in Azure ecosystem, Azure services and data platforms like Databricks.
• It is a serverless and scalable solution for cloud data integration.

Incentivized

• Oracle Database : Deliver industry-leading security, high availability and scalability with Oracle Database, which has been significantly enhanced to take advantage of the Oracle Exadata Storage Servers.
• Exadata Smart Scan : Improve query performance by offloading intensive query processing and data mining scoring to scalable intelligent storage servers.
• Smart Flash Cache : Transparently cache 'hot' read and write data to fast solid-state storage, improving query response times and throughput. Exadata systems use the latest PCI flash technology rather than flash disks. PCI flash delivers ultra-high performance by placing flash directly on the high speed PCI bus rather than behind slow disk controllers.
• Hybrid Columnar Compression : Reduce the size of data warehousing tables by 10x, and archive tables by 50x, to improve performance and lower storage costs for primary, standby, and backup databases. Query high, query low, archive high and archive low.
• Infiniband Network : Connect multiple Oracle Exadata Database Machines using the InfiniBand fabric to form a larger single system image configuration. Each InfiniBand link provides 40 Gigabits of bandwidth–many times higher than traditional storage or server networks.
• Petabyte Scalability : Easily scale data warehouse to support enterprise data growth.

Incentivized

• Granularity of Errors: Sometimes, Azure Data Factory provides error messages that are too generic or vague for us, making it challenging to pinpoint the exact cause of a pipeline failure. Enhanced error messages with more actionable details would greatly assist us as users in debugging their pipelines.
• Pipeline Design UI: In my experience, the visual interface for designing pipelines, especially when dealing with complex workflows or numerous activities, can become cluttered. I think a more intuitive and scalable design interface would improve usability. In my opinion, features like zoom, better alignment tools, or grouping capabilities could make managing intricate designs more manageable.
• Native Support: While Azure Data Factory does support incremental data loads, in my experience, the setup can be somewhat manual and complex. I think native and more straightforward support for Change Data Capture, especially from popular databases, would simplify the process of capturing and processing only the changed data, making regular data updates more efficient

Incentivized

• The process of patching and upgrade of Exadata server components could be improved with a goal to minimize the overall effort, make it fully automated and transparent.
• Improved guidelines and possibly more sophisticated tools for sizing of new Exadata servers for migration from old legacy hardware.

Incentivized

So far product has performed as expected. We were noticing some performance issues, but they were largely Synapse related. This has led to a shift from Synapse to Databricks. Overall this has delayed our analytic platform. Once databricks becomes fully operational, Azure Data Factory will be critical to our environment and future success.

Incentivized

I am comparing Exadata with the Oracle RAC database experience. In addition to Oracle RAC features, Exadata provides automatic performance optimization through Smart Scan and storage indexes. Deep integration with the Oracle ecosystem and tight coupling with Oracle Enterprise Manager
for monitoring and management. Some downsides of Exadata are: a steep learning curve, concepts like cell offloading, IORM, and flash cache behavior aren’t intuitive initially. Operating
Exadata requires specialized DBA skills.

Incentivized

We have not had need to engage with Microsoft much on Azure Data Factory, but they have been responsive and helpful when needed. This being said, we have not had a major emergency or outage requiring their intervention. The score of seven is a representation that they have done well for now, but have not proved out their support for a significant issue

Incentivized

Azure Data Factory helps us automate to schedule jobs as per customer demands to make ETL triggers when the need arises. Anyone can define the workflow with the Azure Data Factory UI designer tool and easily test the systems. It helped us automate the same workflow with programming languages like Python or automation tools like ansible. Numerous options for connectivity be it a database or storage account helps us move data transfer to the cloud or on-premise systems.

Incentivized

Oracle Exadata Database Machine had the best performance overall hands down. It clearly beat the competition and we were seeing 1000X improvement on SAP HANA. Oracle Exadata Database Machine beat that without us refactoring our code. To achieve that in HANA, we had to refactor the code somewhat. Now this was for our limited POC of 5 use cases. Given the large number of stored procedures we had in Sybase, we need to capture more production metrics but we are seeing incredible performance.

Incentivized

• Facilitate better decision-making and improve business processes.
• Optimize business process outcomes by increasing internal efficiency and operational effectiveness.
• Boosts revenue growth while improving business process agility.

Incentivized

• Single support from a single vendor with both machine and database from Oracle, which is costing us less.
• With Exadata, we need less technical manpower and less technical support. A business transaction with the integrated and centralized database helps us focus on other business needs.
• We don't need to buy additional licenses and Hardware for the next 3 to 5 years.

Incentivized