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PostgreSQL query method shows 100M vector performance with less RAM

By PulseAugur Editorial · [1 sources] ·

A new query method for PostgreSQL has been developed, demonstrating impressive performance by handling 100 million vectors using significantly less RAM. This advancement, however, comes with a notable build time and requires a specific, upcoming version of PostgreSQL, indicating it is currently in an alpha stage. AI

IMPACT This development could improve the efficiency of AI applications that rely on large-scale vector databases for tasks like similarity search and recommendation systems.

RANK_REASON The item describes a new technical capability for a database system, which falls under research. [lever_c_demoted from research: ic=1 ai=0.7]

Read on Mastodon — sigmoid.social →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

PostgreSQL query method shows 100M vector performance with less RAM

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4 / 100
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The item describes a new technical capability for a database system, which falls under research. [lever_c_demoted from research: ic=1 ai=0.7]
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. Mastodon — sigmoid.social TIER_1 English(EN) · [email protected] ·

    The query win at 100M vectors on 4x less RAM holds up. The 42-hour build gap is tilted, and the extension is alpha and needs PostgreSQL 18. # postgres # ai # da

    The query win at 100M vectors on 4x less RAM holds up. The 42-hour build gap is tilted, and the extension is alpha and needs PostgreSQL 18. # postgres # ai # database # machinelearning # software # coding # development # engineering # inclusive # community pg_vectorsearch vs pgve…

    LINKS dev.to/…/pgvectorsearch-vs-pgvector-hnsw-…

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