Kumaravel Vivekanandam’s Post

Meanwhile #Fabric offers a very predictable TCO, similar and often faster performance than Databricks and is tightly integrated with Power BI and the Microsoft ecosystem. And best of all, depending on the shape of your workload can work out to be significantly cheaper than either platform! 🧐 Why do these comparisons focus on specific query workloads to compare cost? You need to look at the big picture! No one runs up a Snowflake or Databricks instance to run a couple of queries.

I never really viewed Snowflake as a direct competitor to Databricks; it's perhaps more comparable to Oracle and other traditional cloud-lifted data warehouses. Databricks offers so much more than just a warehouse. At the end of the day, it's the performance and cost-effectiveness, rather than additional features, that ultimately secure large-scale deals. Databricks definitely lands those in spades and more. Now, Fabric - that's much more in the realm of the playing field that Databricks dominates these days. It's exciting to see where this leads next!

Snowflake and Databricks are two powerhouses in data technology, each with unique strengths in data management, analysis, and machine learning. Since I started diving into the Databricks platform, I’ve been curious about how it compares with Snowflake. This post provides a great comparison!

Worth looking into if you are concerned with costs.

Worth reading if you're in the data space or working with Databricks or Snowflake. #databricks #snowflake #dataengineering #dataanalytics"

Stacksync now supports Front! Install the connector to two-way sync Front to data warehouses like Postgres, Snowflake, BigQuery, and more — all in real-time and without code. Install the app on Front: https://buff.ly/3XnHjJi #HubSpot #ReverseETL #ETL #DataEngineering #Sync #RevOps

Guess what? You can use #Fabric #DataPipeline to orchestrate data movement from #Google #BigQuery to #FabricLakehouse, #Warehouse or #KQL Database internally and externally to #SQLServer, #AzureSQL, #SnowflakeWarehouse, #ADLSGen2 to name few. So, it doesn't matter the source of your data and the destination, you can always get your data provisioned for analysis provided you know the connection workaround

Users can quickly implement Elasticsearch on AlmaLinux by following simple installation steps to get robust data management and search features. https://lnkd.in/gVcs4_9Q

Users can quickly implement Elasticsearch on AlmaLinux by following simple installation steps to get robust data management and search features. https://lnkd.in/er8AghKM

Users can quickly implement Elasticsearch on AlmaLinux by following simple installation steps to get robust data management and search features. https://lnkd.in/gvjdSZJT