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Latest updates for Dremio

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dev.to /1 month ago

Why Dremio's Value Is Unique to Apache Iceberg Lakehouses and Agentic Analytics

Most data teams have already made two decisions, even if they haven't written them down yet. The first is that Apache Iceberg will be the table format their analytical data lives i...

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news.sap.com /1 week ago

SAP Completes Acquisition of Dremio

WALLDORF & AUSTIN — SAP has completed the acquisition of the open, high-performance data lakehouse platform.

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dzone.com /1 week ago

Apache Spark Query Optimization on Databricks: Catalyst, AQE, and Photon Engine

Why Query Optimization Matters A Spark query written by a human and a Spark query executed by the engine are often very different things. The gap between them — the optimization —...

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dataengineeringcentral.substack.com /3 weeks ago

Apache Datafusion Comet (Spark Accelerator)

any better than last time?

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dzone.com /1 week ago

Building Production-Grade Delta Lake Pipelines With Apache Spark on Databricks

Why Delta Lake? Apache Parquet on cloud storage was a great first step for data lakes — but it left engineers dealing with a painful set of problems in production: No ACID transa...

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aws.amazon.com /1 week ago

Serverless analytics pipelines using the Apache Spark engine in Amazon Athena

This post shows how developers, data engineers, and analysts can connect to a secure Spark Connect endpoint in Athena with Apache Spark. You can use your preferred tools, such as J...

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rubyflow.com /1 month ago

Databricks Consulting Services by Melonleaf | Data & AI Solutions

Transform your business with expert Databricks consulting services from Melonleaf. We help organizations implement scalable data engineering, lakehouse architecture, machine learni...

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smallbiztrends.com /5 days ago

SAP Acquires Dremio to Enhance Real-Time Data Analysis and AI Capabilities

Discover how SAP's acquisition of Dremio is set to transform real-time data analysis and boost AI capabilities, enabling businesses to unlock deeper insights and drive innovation.

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dzone.com /1 week ago

Azure Databricks for Scalable MLOps and Feature Engineering With Apache Spark, Delta Lake, and MLflow

Raw data doesn't win model competitions. Features do. And when your raw data is tens of billions of rows sitting across multiple sources, you can't afford to run pandas in a notebo...

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dzone.com /6 days ago

Azure Databricks vs Microsoft Fabric: An Honest Guide to When to Use What

If you're building a data platform on Azure in 2026, you're going to be asked this question: Azure Databricks or Microsoft Fabric? Both run on Delta Lake, both integrate with ADLS...

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cloud.google.com /1 month ago

Deep dive: How Lightning Engine delivers 4.9x faster Apache Spark performance

From foundational ETL and analytics to the frontier of generative AI, Apache Spark serves as the architectural backbone for global data processing. However, as data volumes scale,...

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databricks.com /1 month ago

BI Serving Pointers; Maximizing for Performance and TCO

Your BI dashboards are slow, and tuning them is costing too much time and money.It's...

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snowflake.com /1 month ago

The Interoperable Lakehouse: Agency Over Your Data

Achieve true agency over your data with the Snowflake Interoperable Lakehouse. Unify storage, governance, and semantics with managed Apache Iceberg.

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databricks.com /1 month ago

Advancing Apache Iceberg on Databricks: Iceberg v3 GA, Open Sharing, and Unified Governance

The next phase of the open lakehouse will be defined by the catalog. Open table formats...

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snowflake.com /3 weeks ago

Snowflake Postgres Powers Low-Latency ML Feature Serving

Snowflake's ML team chose Snowflake Postgres to power their Online Feature Store — demonstrating 2.5x lower latency and 7x higher QPS than Databricks Lakebase in production benchma...

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theregister.com /1 week ago

Databricks unifies OLTP and OLAP, depending on what counts as a copy

LTAP architecture does some clever engineering beneath a debatable marketing pitch

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databricks.com /1 week ago

Reimagining Data Modeling on the Lakehouse: Introducing Vibe Data Modeling

The challenges with Data ModelingIn every analytics stack, the Silver layer is where...

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dzone.com /1 month ago

Rust-Native Alternatives to Spark SQL and DataFrame Workloads

Apache Spark is one of the most powerful tools in the data and AI engineering world. It helps process massive datasets and is widely used across industries, irrespective of cloud p...

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dev.to /1 month ago

Performance and Apache Iceberg's Metadata

This is Part 3 of a 15-part Apache Iceberg Masterclass. Part 2 covered the metadata structures of all five table formats. This article focuses on exactly how query engines use Iceb...

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databricks.com /1 month ago

Bring Databricks into Kiro IDE with the AI Dev Kit Power

Why this mattersAI-assisted development falls apart the moment the assistant has to guess at column names, table layouts...

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aws.amazon.com /1 week ago

Accelerating log analytics at scale with AWS Glue and Apache Iceberg materialized views

In this post, you learn how to build an application log pipeline for production use with Amazon CloudWatch Logs, AWS Lambda, Amazon Data Firehose, AWS Glue, and Apache Iceberg mate...

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blogs.vmware.com /4 weeks ago

Embracing Schema Drift: Seamless Parquet Querying in Tanzu Greenplum, No Matter How Your Data Changes

<div><img width="300" height="157" src="https://blogs.vmware.com/wp-content/uploads/2026/06/vmw-blogtile-tanzu-greenplum-v2_fzmxrz.png" class...

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medium.com /1 week ago

10 SQL Techniques for Implementing Custom Materializations in Modern Data Warehouses

Practical materialization strategies that improve query performance, freshness, and warehouse scalabilityContinue reading on Medium »

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aws.amazon.com /4 weeks ago

Improve query performance with EXPLAIN plans in Amazon Aurora DSQL

In this post, we show you how to use EXPLAIN plans to diagnose and improve query performance in Amazon Aurora DSQL. We introduce a three-layer filter model as a practical framework...

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