Incumbent Warehouses Ease Streaming Procurement

Bundling turns real time analytics from a new platform decision into a small extension of an existing warehouse deal. In a big enterprise, that matters as much as raw query speed. Snowflake, BigQuery, and Redshift already sit inside approved budgets, security reviews, and data pipelines, so a team can add streaming ingestion and fresher dashboards without asking procurement to onboard a separate vendor like ClickHouse.

• The practical advantage is workflow, not just pricing. Snowflake offers Snowpipe Streaming for low latency ingestion into the same system used for warehousing. BigQuery makes streamed rows queryable right after acknowledgement. Redshift ties streaming and zero ETL analytics into the broader AWS stack. That lets buyers extend an existing contract instead of opening a new database evaluation.
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• ClickHouse still wins where sub second performance is the product. At AstraZeneca, Snowflake remained the governance and reporting layer while ClickHouse handled fast analytics and AI retrieval. That split shows why incumbents are sticky in central data platforms, even when a specialist engine is better for the speed layer.
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• Databricks is the same pattern from a different starting point. It now offers real time mode in Structured Streaming and serverless streaming tables, so teams already running ML, feature engineering, and lakehouse workloads can add lower latency processing inside an existing Databricks footprint rather than carve out a separate ClickHouse deployment.
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The next phase is less about whether warehouses can match ClickHouse on absolute speed, and more about whether they get close enough for most enterprise buyers. As open table formats reduce storage lock in, ClickHouse has a better shot at landing one workload at a time, but incumbents will keep defending the account by folding real time features into the broader warehouse contract.