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Everything / Data and databases / Text to SQL

Trend in Data and databases · tag text-to-sql · through Sep 2026

Text to SQL Growing

On TutorHero's Everything Index, Text to SQL is growing on GitHub: 0.22 of every 10,000 new public repos over the last three months (208 a month), 7x vs a year ago. The 12-month forecast says rising (+88%). By the end of 2032, lines in the same state ended between 0.01x and 2.5x of where they started (median 0.54x).

Per 10k new repos0.22208 new repos a month
Year over year7x3 months: +50%
Next 12 months+88%80% band +58% to 6x
2032, median of history0.54x90% of past cases: 0.01x to 2.5x
Attention0.13%of new stars, -78% in a year
Jev 2032 callnot read yetonly top trends are sent to Jev
Share on X

Since 2019, and the range to 2032

0.010.030.10.31320192020202120222023202420252026202720282029203020312032Range to 2032 (history of similar lines)Stable Diffusion releasedChatGPT launchesGPT-4Llama 2, open weightsModel Context ProtocolDeepSeek-R1Claude Code previewHigh 0.54Median 0.12Low 0.00

New repos per 10,000 (3-month average, log scale)12-month forecastRange to 2032: middle half and 90% of past similar lines

The range is not a forecast of this line: it is what GitHub lines in the same state (more than doubled its share of new repos in a year) did 1 to 5 years later, 2019 to 2026, applied to today's level. Past 5 years it is stretched, not measured. Checked out of time (learned before 2022, scored after), 71% of outcomes landed inside the 90% range, so read it as wide. Open it in the Everything chart.

Week by week

Last week166 new reposOct 12 to Oct 18 · +41% against the field
Last 4 weeks▲ +37%386 new repos, against the 4 weeks before and the field
AprMayJunJulAugSepOct

New public repos with the text-to-sql tag each week (Monday to Sunday, UTC). The outlined bars, last week included, are still filling in, as tags are often added days after a repo is created, so their height will grow a little. "Against the field" divides the change by what the typical tag did, so a wave that lifts every tag does not count. Hover for the numbers.

Built vs talked about

Hacker News2 stories a month+141% share of HN vs a year ago · titles with "text-to-sql"

Each line is its own share (of all new GitHub repos, all Hacker News stories, all English Wikipedia views, all new stars on the repos we track), shown as a share of its own peak, so the timing and shape compare even though the units differ. Hover for the counts. Tap a name to hide or show a line.

What it means

Studentslearning it, contributing, getting hired
  • Worth learning now: Text to SQL is growing, 7x share of new GitHub repos vs a year ago.
  • Start by reading Canner/WrenAI (+393 stars in 3 months) and OtterMind/Chat2DB (+299 stars in 3 months).
  • People to follow: Agno.
Founders and builderswhat to build next
  • Getting crowded: new repos 7x but attention -78%, so each new project competes harder for stars.
  • 2.20 new stars per new repo over 3 months, vs 8.50 for the typical trend: more supply than demand right now.
  • The 12-month forecast for its share: +88% (Rising).
Investorswhich fields deserve research time
  • History: of past GitHub lines that more than doubled its share of new repos in a year, 61% had a smaller share 3 to 5 years later and 8% at least doubled.
  • Attention: 0.13% of new stars on the repos we track, -78% in a year.
  • Hacker News: 2 stories a month, +141% share in a year.
  • Not investment advice: this measures what people build on GitHub, not any company.
Developers choosing toolswhich tools to adopt
  • Most-starred tools here lately: Canner/WrenAI (organic stars), OtterMind/Chat2DB (organic stars).
  • The field is growing, so expect new tools and fast changes; pin versions.

Repos carrying it now

Canner/WrenAIGenBI (Generative BI) for AI agents, an open-source, governed text-to-SQL through an open context layer that turns natural-language question+393 stars in 3 months · organic
OtterMind/Chat2DBChat2DB is a free, cross-platform, local-first database client and SQL workspace for developers, DBAs, analysts, and data teams. Connect to +299 stars in 3 months · organic
dataease/SQLBot🔥 基于大模型和 RAG 的智能问数系统,对话式数据分析神器。Text-to-SQL Generation via LLMs using RAG.+155 stars in 3 months
getnao/nao👾 nao is an open source analytics agent. (1) Create context with nao-core cli, (2) deploy nao chat interface for everyone+129 stars in 3 months · organic
sinaptik-ai/pandas-aiChat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.+63 stars in 3 months
Sheltercosmo/jev4pgEstablished strong JEV based natural language to SQL performance and well-covered semantic operators for PostgreSQL(PG) with optimized cost +48 stars in 3 months · new

People building it

More in Data and databases

Questions

Is Text to SQL growing on GitHub?

Yes. Its share of all new public GitHub repos is 7x vs a year ago and +50% over the last three months (Sep 2026). Phase: Growing.

How many new Text to SQL repos are created each month?

About 208 new public repos a month carry the text-to-sql tag (three-month average to Sep 2026), or 0.22 of every 10,000 new repos.

What will Text to SQL look like in 2032?

Nobody knows, and we say how much. Of past GitHub lines that more than doubled its share of new repos in a year, the middle half had between 0.14x and 1.27x of their share 3 to 5 years later, and 61% ended smaller.

Not investment advice. Measurements of what people build and star on GitHub, a statistical forecast, base rates and a model's reading of them. Nothing here is about any company's revenue, valuation or stock.