The past, present and future of data warehouse appliances

Senior Offering Manager, IBM

Since the first data warehouse appliance was introduced, there have been people eager to claim that the technology had outlived its usefulness and would soon become extinct. The latest iteration of this hackneyed outlook took aim at Netezza specifically, as unscrupulous vendors attempted to exaggerate the significance of TwinFin and Striper’s end of support (EoS) starting in June 2019.

Yet Netezza, much like the data warehouse appliance itself, has a vibrant future to match its storied past thanks to the IBM Integrated Analytics System. The solid Netezza foundation of performance and reliability is evolving to meet today’s demanding needs for hybrid cloud, machine learning and data science. For that reason, it’s important to take a holistic look at the past, present, and future of the data warehouse appliance along with Netezza’s continued role.

Data warehouse appliance origins

As Claudia Imhoff details in her article, “Data Warehouse Appliances and the New World Order of Analytics,” companies had started loading data into on-premises “black boxes” and attaching business intelligence (BI) technologies onto them in the early 2000s.

Since then, Netezza announced the industry’s first true “data warehouse appliance,” rapidly increasing a user’s ability to collect data, with core strengths of simplicity, speed and low cost of ownership. Netezza would go on to support major programming languages, including Hadoop MapReduce, Java, C++ and Python, continuing to deliver considerable value to those who embrace its potential.

Today, companies continue to enjoy keeping their data and analytics on-premises with an integrated software and hardware platform. It reduces the time, skills and vendors required to purchase hardware and software components, test integrations and tune the system for optimal performance.

Companies with sensitive workloads and security, privacy or regulatory compliance requirements can also feel more comfortable housing their data on premises. For this reason, the data warehouse is still a great option for reliable, consistent, integrated and high-quality data for critical or sensitive analyses, especially for financial, compliance or regulatory requirements.

Bright future

In September 2017, IBM introduced its next-generation data warehouse appliance, the IBM Integrated Analytics System (IIAS), which builds upon Netezza’s legacy. In doing so, IBM once again challenged the status quo in the hybrid data warehouse market by delivering outstanding performance, value and new capabilities to its customer base.

This unique, cloud-ready appliance and machine learning platform wields the power of an in-memory, massively parallel processing database engine with embedded Spark. It also runs on market-leading IBM Big Data Servers and IBM FlashSystem 900 storage arrays enabling a high-performance system optimized for business insight as well as advanced operational and in-database analytics. While the technology built into the appliance is impressive, what makes it truly stand out is the core hybrid data management strategy that anchors it.

A clear path to the cloud with Netezza

Few businesses are taking an all-on-premises or all-cloud approach. Most are blending the two in varying amounts and at the speed which makes sense based on company size, industry, maturity, complexity and data sensitivity. In recognition of this, the IBM Integrated Analytics System uses the IBM Common SQL Engine, which delivers query and application compatibility along with data integration and virtualization across IIAS and the IBM Db2 family of offerings, whether they’re on premises or on cloud. It also extends to competitive data sources such as Oracle, Teradata and Microsoft SQL Server, cloud sources such as Amazon redshift and open source solutions such as Hive. This allows users to “write once, run anywhere” and make use of prior investments in SQL skills.

As a result, we’re seeing customers take two different strategies. Many businesses are taking a gradual approach, experimenting with moving certain workloads to the cloud while still maintaining an appliance for more sensitive data. The cloud-ready IBM Integrated Analytics System appliance facilitates this by enabling users to shift workloads between public or private clouds and on-premises environments based on application requirements.

Other businesses are looking to move to the cloud quickly, and that is supported, too. After mapping out their hybrid management strategy, many are seeing the value of interoperability between the IBM Integrated Analytics System and Db2 Warehouse on Cloud. Db2 Warehouse on Cloud is an elastic, fully managed cloud data warehouse service powered by IBM BLU Acceleration technology for increased performance and optimization of analytics at a massive scale.

Despite what the naysayers might have you believe, Netezza and the data warehouse appliance live on in the spirit of the IBM Integrated Analytics System. To learn more, listen to the latest webinar, “The Future of Data Warehousing, Data Science and Machine Learning with the IBM Integrated Analytics System.

Join me for my next post, in which I will explain why your organization should start down the path to machine learning and data science now.

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