Azure Synapse Analytics vs. Oracle Data Integration Platform Cloud (DIPC)

It's well suited for large, fastly growing, and frequently changing data warehouses (e.g., in startups). It's also suited for companies that want a single, relatively easy-to-use, centralized cloud service for all their data needs. Larger, more structured organizations could still benefit from this service by using Synapse Dedicated SQL Pools, knowing that costs will be much higher than other solutions. I think this product is not suited for smaller, simpler workloads (where an Azure SQL Database and a Data Factory could be enough) or very large scenarios, where it may be better to build custom infrastructure.

Incentivized

For daily transactional information and customer data needs it has been an extremely fast and reliable system. Several thousand users are able to connect many third party tools and run a large number of extracts while still experiencing great performance. For smaller systems in use with limited user accounts this system is less appropriate due to maintenance resources required.

Incentivized

• Create data pipelines to connect with multiple data workspace(s) and external data
• Ability to connect with Azure Data Lake (sequentially) for data warehousing
• Being able to manage connections and create integration runtimes (for onPrem data capture)

Incentivized

• ODI uses ELT architecture, which enhances the load performance and is very scalable.
• ODI is platform independent. It supports all platforms, hardware and operating systems.
• It comes with pre-built integration, allowing immediate data replication, transformation, and data governance while ensuring data quality.

Incentivized

• It takes some time to setup a proper SQL Datawarehouse architecture. Without proper SSIS/automation scripts, this can be a very daunting task.
• It takes a lot of foresight when designing a Data Warehouse. If not properly designed, it can be very troublesome to use and/or modify later on.
• It takes a lot of effort to maintain. Businesses are continually changing. With that, a full time staff member or more will be required to maintain the SQL Data Warehouse.

Incentivized

• Training and ramping up to learn all the Oracle specific intricacies.
• Security concerns with administering some of the tools to end users.

Incentivized

The data warehouse portion is very much like old style on-prem SQL server, so most SQL skills one has mastered carry over easily. Azure Data Factory has an easy drag and drop system which allows quick building of pipelines with minimal coding. The Spark portion is the only really complex portion, but if there's an in-house python expert, then the Spark portion is also quiet useable.

Incentivized

Microsoft does its best to support Synapse. More and more articles are being added to the documentation, providing more useful information on best utilizing its features. The examples provided work well for basic knowledge, but more complex examples should be added to further assist in discovering the vast abilities that the system has.

Incentivized

When client is already having or using Azure then it’s wise to go with Synapse rather than using Snowflake. We got a lot of help from Microsoft consultants and Microsoft partners while implementing our EDW via Synapse and support is easily available via Microsoft resources and blogs. I don’t see that with Snowflake

Incentivized

We are longtime ODI on-premise users. So, it was easy for us to migrate to the ODI cloud rather than implementing another solution.

Incentivized

Basically, the billing is predictable, and this all about it.

Incentivized

• We have had an improvement in our overall processing time
• Cost was much lower than most of its competitors
• Our reporting needs have grown and housing the data here has been great

Incentivized

• Ability to setup reliable disaster recovery.
• Upgrades and performance monitoring tools are readily available.

Incentivized