Apache Doris – A Faster, Smarter, and Stabler Database

Hacker News

What makes it worth knowing about? 1. A query optimizer that is more effective than human optimization 2. Faster log queries with less storage space consumed (compared to Elasticsearch) 3. 20 times higher concurrency (30,000 QPS per node) 4. Enhanced Data Lakehouse capabilities (more data sources supported and faster performance) 5. A self-adaptive parallel execution model for higher efficiency and stability in hybrid workload scenarios 6. Better management of memory and CPU resources 7. Elastic scaling of computation resources and hot-cold data separation for much lower storage costs 8. Faster, stabler, and smarter data ingestion 9. No more OOM errors 10. Support for Kubernetes deployment https://doris.apache.org/docs/dev/releasenotes/release-2.0-beta/

Visit product View on Hacker NewsJul 5, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, notes · Missing: mac, agents, macos

75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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Indie HackersFits the IH revenue-focused audience · Strong signals: para, ios · Missing: supports, reddit linkedin, podcasting

71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: 000, io · Missing: https docs, excited, just released

67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: ios, para · Missing: mobile apps, personal, entrepreneurs

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

24%24% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto

9%9% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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