Is It Too Late For Oracle to Enter the Cloud Analytics Space?

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So Oracle has officially entered the cloud analytics space. Building off the announcement at Oracle Open World last fall, yesterday they officially released their autonomous data warehouse for the cloud. And it’s a big deal for them. Built on their latest 18c database, the autonomous data warehouse brings the potential for a new level of simplicity. It leverages machine learning to ensure constant uptime by automatically (hence “autonomous” everywhere in their announcement) protecting, securing, and repairing the database. On top of the promised simplicity, they tout the ability to lower costs and perform faster than the competition. OK, Oracle, well played. I’m intrigued, maybe even a little excited, but the reality is that Oracle is still behind. They (self-admittedly) lost the cloud infrastructure war, and I’m nervous that they could lose this one too if they don’t play their cards right.

Of the areas where Oracle has an uphill battle, here are three that are top of mind for me…

  • Late to market - The cloud analytics and big data space is crowded and hyper-competitive. You have hyper-scale cloud giants AWS, Google Cloud Platform, and Microsoft Azure that already have mostly complete data platforms containing all the services most organizations may need (PaaS), with updates and new services popping up regularly. You have point players that leverage those hyper-scale cloud providers (IaaS) to build single service solutions (SaaS) – think incumbents like Snowflake or insurgents like Panoply for smart cloud data warehouses only. You even have newer companies that are looking to burst onto the scene like Starburst Data who are building on Presto, which decouples storage and compute in the cloud. Clearly, Oracle faces no shortage of competitive providers and offerings in this market, but the company does have the necessary assets -- technology chops, services, support, a powerful sales/marketing engine and war chest – with which to go to battle.
  • Migration is hard – This is a two-fold problem for Oracle. First, there are those customers that are still on-premises only and looking to move to the cloud, but adopting a new consumption model is a challenge. Second, there are those organizations that have already committed to other cloud data platforms, migrated their data, and are already seeing business value. Moving cloud-resident data between clouds can be an expensive task. However, this is where Oracle can exploit one of the key advantages they have over other cloud analytics competitors – i.e., their inherently hybrid (both on- and off-premises) capabilities. In other words, Oracle has a large existing customer base looking to transform from a legacy architecture to a cloud architecture, while continuing to utilize Oracle. Oracle can service these customers very effectively while also looking to attract new hybrid buyers that don’t want to put all their eggs in the public cloud basket.
  • Promising the best price/performance in the cloud is tricky – different pricing models, discount options, and price cuts across cloud providers on a regular basis make it really hard to guarantee the best price/performance. Providing credible and publicly available pricing and performance results, case studies, and price/performance calculators will all serve Oracle well as they look to become the leader in the ever-changing cloud price/performance war.

Now don’t get me wrong, Oracle is late to the cloud analytics party, but if they execute to their capabilities, then they will emerge as another powerful offering in the space. They have the leadership, the technology, and the vision to create a powerful data platform in the cloud that competes with the incumbents, but we will be watching closely for adoption proof points, customer testimonials and - most importantly – the actual complete data platform aspects they promise.

Welcome to the party Oracle -- time to grab some popcorn and watch how this unfolds.

Topics: Data Platforms, Analytics, & AI Cloud Services & Orchestration