Databricks Runtime
PulseAugur coverage of Databricks Runtime — every cluster mentioning Databricks Runtime across labs, papers, and developer communities, ranked by signal.
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Databricks integrates native vector search into Databricks Runtime
Databricks has introduced a new vector search capability directly within its Databricks Runtime, designed to optimize batch-oriented vector search workloads. This feature, called NEAREST BY Join, integrates vector searc…
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Databricks enables on-demand state repartitioning for Apache Spark Structured Streaming
Databricks has introduced On-Demand State Repartitioning for Apache Spark Structured Streaming, a new feature available in Databricks Runtime 18 and above. This capability allows users to resize the number of partitions…
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Databricks enables local IDE development for data and ML workloads
Databricks has enhanced its IDE integration, allowing developers to run, debug, and scale workloads directly from their local development environments. This update enables connections to Databricks compute, including Se…
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Databricks Auto Upgrades enhance Unity Catalog tables without manual effort
Databricks has introduced Auto Upgrades, a new feature designed to automatically apply best-practice enhancements to Unity Catalog managed tables. This system verifies workload compatibility before enabling features lik…