Engineer at Google LLC (Alphabet Inc)
- Google BigQuery’s (NASDAQ: GOOGL) overall operating environment and data warehouse sector trends, highlighting Omni product
- Competitive dynamics among Google BigQuery, Amazon (NASDAQ: AMZN) Redshift, Azure Synapse (NASDAQ: MSFT), Snowflake (NYSE: SNOW) and more
- Open-source technologies and newer vendor threats, partner strategies and product innovation
- H2 2022 outlook and the probable recessionary environment’s impact on customer spend
Can you give an overview of Google BigQuery and its overall operating environment, pulling 2-3 key trends or drivers that you think are most important for investors to monitor for the business in the data warehousing sector?
What key headwinds or tailwinds are impacting demand for data warehousing? To what extent did coronavirus increase enterprises’ interest in cloud-based analytics? How much of that do you think was a pull-forward in demand vs a permanent, step-function increase in demand for these types of solutions?
The transformative aspects of BigQuery and data housing for an enterprise seem to make demand pretty inelastic among customers. Why is that? How do you think demand for these cloud-based analytics products and data warehousing broadly will trend over the next 12-18 months if we enter a flat-to-downward-performing market, as we’re seeing signs of a probable recession incoming?
Amazon Redshift’s serverless seems to now be online and it was announced in 2021. To what extent do you see serverless changing the competitive landscape for data warehouses? How are the hyperscalers positioned with that shift?
How long could it take for Redshift to reach a competitive parity with BigQuery along the lines you discussed?
What percentage of the overall Fortune 1000’s corporations may be adopters of a data-warehousing or data-cloud product today vs 1-2 years ago? What is the adoption curve’s intensity among corporations?
Do you agree that BigQuery is perhaps a better product vs Redshift and Azure Synapse, given its better architecture? You spoke about BigQuery’s products and functionality relative to those of Redshift. Why might BigQuery hold an edge over Redshift and Synapse and why haven’t other providers been able to catch up? How quickly might that gap be closing?
Do you think the Omni product is as functional as the pure-play BigQuery? It went live with BigQuery in 2020. Do you think customers are picking Omni as their main play more or less often than just the pure-play BigQuery product? How much market penetration might Omni have?
What investment or intensity do you think would have to go into Omni to make it more killer in Google’s eyes? Thinking about the customers on AWS, you seem to be saying Snowflake still has an advantage in the multi-cloud environment. Do you think Omni can reach that competitive parity and be a differentiator for Google, or is it a bit too far off to tell?
You mentioned that Omni still doesn’t have the same functionality as Snowflake. What investment do you think could be required by BigQuery to close that gap? Is it a question of investment in Omni or is it investment in completely new features or products to bring it up to parity in other areas and to better close the overall gap between BigQuery and Snowflake?
You mentioned Redshift seems to be pretty cost-competitive while still building out new features relatively aggressively. What are your thoughts around BigQuery offering on-demand and flat rate pricing structures to customers? How does that shift that usage pattern in TCO [total cost of ownership]? Does the on-demand pricing run up the TCO for BigQuery customers and potentially take away some of Google’s cost-competitiveness? How important is that in this landscape?
You mentioned reducing the ROI calculation and TCO. How are you assessing the other new product releases for BigQuery? How do you think Google will continue to innovate and augment on the products, such as the release of BigLake in April 2022? Do you think the goal with new releases is just to increase the use cases or improve the ROI calculations the customers are undertaking, because BigQuery is thought to be the cheaper solution and we’ve discussed maintaining that edge? What do you think the overall focus and strategy is for the product roadmap?
On AWS’s ability to catch up with Redshift, do you think the data warehouses that leverage AWS Compute – so Redshift and Snowflake – will be in a better competitive position over the next few years given the new chip designs that AWS is deploying? The company seems to have better cost performance related to other in-house chips and other chips in the market. Do you consider that a competitive advantage in the long term?
On BigQuery’s key features, you mentioned GIS [Geographic Information System] and BigQuery ML [Machine Learning] but we didn’t mention BI [Business Intelligence] Engine. What stands out as the most important or best product from a functional perspective in customers within that suite? What has a defining competitive edge across BigQuery’s suite, comparing the key features head-to-head vs others available in the market? Is it still the pure-play platform or are any of the other pieces picking up any slack for the company in the competitive landscape?
Can you speak about the broader strategy at GCP [Google Cloud Platform], in terms of investment into channel partners to grow? How important do you think that is for Google to take ownership of and increase the reliance and strength of its system’s integrative partnerships for implementation and tech partners for integration? Would you expect the company to continue to invest in those lines, or is this currently less important than augmenting the product and improving the features? We talked about the increased investment and high retention for the product.
Is there anything we haven’t covered or are there any key risks for BigQuery that we should monitor?
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