Azure Synapse Analytics vs. IBM Netezza Performance Server

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.

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We can query the data source and treat multiple databases
as one with IBM Netezza Performance Server.



While delivering fast and reliable analytical performance, the IBM Netezza Performance Server requires minimal configuration and ongoing
management.



To drive organizational performance, Netezza Performance
Server automatically simplifies data and AI to centralize all analytics
activities on the device, exactly where the data resides.



For data processing and application dashboards, IBM Netezza
Performance Server is quite beneficial.





IBM Netezza Performance Server simplifies event setup
by notifying you when a hardware component fails, allowing you to quickly
replace it.

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• Quick to return data. Queries in a SQL data warehouse architecture tend to return data much more quickly than a OLTP setup. Especially with columnar indexes.
• Ability to manage extremely large SQL tables. Our databases contain billions of records. This would be unwieldy without a proper SQL datawarehouse
• Backup and replication. Because we're already using SQL, moving the data to a datawarehouse makes it easier to manage as our users are already familiar with SQL.

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• IBM Netezza Performance Server enables capabilities to integrate with leading ETL solutions.
• Data can be exported from the IBM Netezza Performance Server to a variety of formats, including Excel.
• We can prioritize specific users and queries using IBM Netezza Performance Server.

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• With Azure, it's always the same issue, too many moving parts doing similar things with no specialisation. ADF, Fabric Data Factory and Synapse pipeline serve the same purpose. Same goes for Fabric Warehouse and Synapse SQL pools.
• Could do better with serverless workloads considering the competition from databricks and its own fabric warehouse
• Synapse pipelines is a replica of Azure Data Factory with no tight integration with Synapse and to a surprise, with missing features from ADF. Integration of warehouse can be improved with in environment ETl tools

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• More tech support may make it easier as it is only limited to be done via company representatives
• Overhead cost for replacements and services looks like it is high compared to others
• Integration with other cloud based application will be great

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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.

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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.

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In comparing Azure Synapse to the Google BigQuery - the biggest highlight that I'd like to bring forward is Azure Synapse SQL leverages a scale-out architecture in order to distribute computational processing of data across multiple nodes whereas Google BigQuery only takes into account computation and storage.

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Netezza is sufficient against similar products. It comes down to personal preference, I'd love to have the data objects popping up as I type but some people may not like it.

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

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• Licensing fees is replaced with Azure subscription fee. No big saving there
• More visibility into the Azure usage and cost
• It can be used a hot storage and old data can be archived to data lake. Real time data integration is possible via external tables and Microsoft Power BI

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• The appliance is all in one so we have all licenses and support contracts under one roof.
• The cost is expensive so ROI may take time to be realized.
• If done correctly, then Netezza provides the opportunity for huge ROI.

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