ETR Observatory Feedback Panel

ETR Insights presents a panel discussion with four veteran IT executives from the ETR Community. The panel was designed to capture feedback and additional insights related to our recent Observatory report and accompanying data set on Cloud Data Warehouses.

Panelists describe a tenuous loyalty to legacy vendors like Teradata and Cloudera in the face of rapid development by Snowflake, Databricks, and Microsoft Synapse; cloud-native services offer more scalable data processing and real-time analytics, and some legacy vendors are ill-equipped to support generative AI, though any migration will be costly. Snowflake and Databricks are undisputed technical leaders, though Microsoft remains most desired on its ecosystem, security, and proven track record. ROI will come from faster analytics, better business decisions, and cost savings from a reduced on-premises footprint, though all panelists prefer a multi-cloud architecture to avoid vendor lock-in. Read on for more on real-time data streaming use cases, private GPTs, low-code platforms, and why data mesh models may ultimately replace data warehouses entirely.

ETR Data: Microsoft Azure Synapse, Databricks, Snowflake, and Amazon Redshift occupy the Leading vector in the ETR Observatory for Cloud Data Warehouses, reporting both high Momentum and high Presence. Google BigQuery lies just over the boundary in the Advancing vector, with higher Momentum but a slightly lower Presence relative to its other hyperscaler competitors.

Key Takeaways

• On-premises vendors pushing for cloud data warehouse adoption. Established on-premises vendors are continuing to lure customers to cloud data warehousing options with some success. But cloud-native data warehousing options are generally seen to be better choices on the whole. Still, the established on-premises players have a role to play, particularly in how they support use cases that can’t be easily replaced in a different vendor’s ecosystem. Hybrid, multi-vendor approaches seem inevitable for most organizations.

• Cost and entanglement drive stickiness. Ease of migration is an important factor in deciding to change a data warehouse. Cost savings and ROI are equally important, but the cost of moving needs to be justifiable.

• Supporting AI initiatives. Snowflake and Databricks are leaders in supporting AI initiatives, but the Big Three public cloud platforms offer seamless integration with broader ecosystems.

See the full Panel summary for direct end-user commentary on vendor preferences, stickiness, ROI, the role of AI on cloud data warehousing, supporting real-time streaming data use cases, future innovations for data mgmt, and so much more.

Enterprise Technology Research (ETR) is a technology market research firm that leverages proprietary data from our targeted IT decision maker (ITDM) community to provide actionable insights about spending intentions and industry trends. Since 2010, we have worked diligently at achieving one goal: eliminating the need for opinions in enterprise research, which are often formed from incomplete, biased, and statistically insignificant data. Our community of ITDMs represents $1+ trillion in annual IT spend and is positioned to provide best-in-class customer/evaluator perspectives. ETR’s proprietary data and insights from this community empower institutional investors, technology companies, and ITDMs to navigate the complex enterprise technology landscape amid an expanding marketplace. Discover what ETR can do for you at www.etr.ai