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“#DataEngineering”×All Time×

Data engineering market shifts as industry consolidation hits record levels

A review of data engineering acquisitions from 2022 to 2026 reveals a pattern of platform consolidation that reshapes how teams build their tech stacks.

#StartupsEntrepreneurship#Engineering#Acquisitions

Jun 18, 20261m readAI

Hacker News: Newest

Databricks maintains $188B valuation as enterprise AI demand grows

Trending

🤖 Technology

Databricks maintains $188B valuation as enterprise AI demand grows

Databricks maintains a $188B valuation as it leans into AI cost-efficiency, though the long-delayed path to an IPO continues to loom over its future strategy.

Jul 17, 20261m readAI

TechCrunch

HeteroDB releases PG-Strom update for GPU and NVMe acceleration in PostgreSQL

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💼 Business & Finance

HeteroDB releases PG-Strom update for GPU and NVMe acceleration in PostgreSQL

HeteroDB’s PG-Strom extension aims to supercharge PostgreSQL with GPU and NVMe hardware acceleration, raising questions about its practical integration for standard database workloads.

Aug 31, 20261m readAI

Hacker News: Newest

Defining the data semantic layer: bridging raw storage and business logic

Trending

💼 Business & Finance

Defining the data semantic layer: bridging raw storage and business logic

A deep dive into how data semantic layers provide a single source of truth for business metrics and the common integration challenges companies face when implementing them.

#StartupsEntrepreneurship#DataEngineering#SemanticLayer

Jun 18, 20261m readAI

Hacker News: Newest

Spice.ai releases v2.0 of its data and AI engine with real-time analytical query support

Trending

💼 Business & Finance

Spice.ai releases v2.0 of its data and AI engine with real-time analytical query support

Spice.ai launches v2.0 of its open-source engine, enabling SQL and LLM-inference directly on operational data without the need for traditional ETL pipelines.

VentureBeat report highlights AI agent reliability gaps in enterprise workflows

VentureBeat reports that AI agents are struggling with factual accuracy in enterprise settings, raising questions about whether a missing context layer is to blame for these persistent errors.

#Startups#EnterpriseAI#AIAgents

Jun 15, 20261m readAI

VentureBeat