Ti

TiDB 1.0 is production ready

Hacker News

TiDB 1.0 is production ready

Two and a half years ago, Edward, Dylan, and I started this journey to build a new database for an old problem that has long plagued the infrastructure software industry. Today, we are proud to announce that this database, TiDB, is production ready. Abraham Lincoln once said, ‘the best way to predict the future is to create it.’ The future we predicted 771 days ago we now have created, because of the hard work and dedication of not just every member of our team, but also every contributor, user, and partner in our open source community. Today, we celebrate and pay gratitude to the power of the open source spirit. Tomorrow, we will continue to create the future we believe in.

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Indie HackersFits the IH revenue-focused audience · Strong signals: created, started · Missing: supports, reddit linkedin, podcasting
85%85% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, open · Missing: mac, agents, macos
78%78% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: open source, io · Missing: https docs, excited, just released
76%76% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal
50%50% 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
22%22% 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
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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