最も「最高」 AI database” roundups are just old no-code tool lists with the word “AI” bolted onto the intro. Half the tools on them can barely autofill a cell, let alone build you a working system from a sentence.
これはそのリストではありません。
We spent real hours inside each of these platforms, building CRMs, running batch generation on a few hundred records, wiring up automations, and pushing the AI until it either delivered or fell over. The question that decided every ranking was simple: does the AI actually do work you would otherwise pay a person to do, or is it a glorified formula wearing a trench coat?
Eight tools cleared that bar. One of them, Teable, pulled ahead of the pack by being genuinely AI-native, open source, and priced in a way that does not punish you for using the features you came for. It sits at number one, and by the end of this piece you will understand exactly why.
What Actually Makes a Database an “AI Database”?
An AI database is a no-code or low-code data platform where 大規模な言語モデル are built into the core workflow, not stapled on as an afterthought. Instead of manually designing tables, tagging rows, and writing formulas, you describe what you want in plain language and the platform builds structures, enriches records, answers questions about your data, and automates the follow-up.
The strong ones share four traits. They build tables and fields from a natural language prompt. They run AI at the cell level to classify, summarize, extract, or generate. They let you query your data conversationally without touching SQL. And they turn that data into apps, dashboards, or automations that keep running after you close the tab.
The weak ones stop at “AI ライティングアシスタント” and call it a day. That distinction is the spine of this ranking.
How We Ranked These 8 AI データベースツール
We scored every platform on five things, weighted toward what a real operator cares about:
Here is where they landed.
おすすめ！ AI Database Tools 2026: Quick Comparison
| ツール | 以下のためにベスト | AI モデル | 開始価格 | オープンソース |
|---|---|---|---|---|
| ティーブル | AI-native database at fair prices | Multi-model (154 LLMs) | Free; Pro $10/seat/mo | Yes (AGPL) |
| Airtable | 最も強力 AI agents, big budgets | GPT, Claude via Bedrock | Free; Team $20/user/mo | いいえ |
| 概念 | AI database inside an all-in-one workspace | GPT-5.2, Claude, Gemini 3 | Free; Business $20/user/mo | いいえ |
| スマートスイート | AI work OS for operations teams | Multi-model agents | Free; Team ~$10/user/mo | いいえ |
| スタックビー | Value pick, bring your own AI key | BYO (OpenAI, Gemini, Claude) | Free; Economy ~$5/user/mo | いいえ |
| ベースロー | オープンソース AI you can self-host | Configurable, local Ollama | Free; Premium ~€5/user/mo | Yes (MIT) |
| ヒューズベース | AI database plus client portals | プロプライエタリ AI エージェント | Trial only, then quote | いいえ |
| ノコDB | AI-ready UI over your existing SQL DB | 新興の | Free self-host; Plus ~$9/seat | ソースコードあり |
1. ティーブル： AI Database Agent That Earns the Top Spot
Teable is what happens when someone builds an AI database from the database up instead of gluing a chatbot onto a spreadsheet. Under the hood it runs on PostgreSQL, which means it handles millions of rows without the lag that makes tools like Notion crawl at scale. On top of that sits an AI エージェント that builds the whole thing for you.
Type “build me a CRM with lead status and follow-up dates” and it creates the tables, fields, and relations in seconds. No template hunting, no field configuration, no learning curve.
That talk-to-build flow is the headline, but the depth is what keeps it at number one. AI fields run inside individual cells to auto-tag, classify, summarize, and enrich data as it lands, with a menu of 154 language models and 17 image models to pick from.
AI Chat lets you interrogate your data in plain English and get charts and reports back. The app builder turns any table into a live web app, dashboard, or ランディングページ connected to real data, not a static mockup. Backed by ZhenFund and Baidu Ventures, with over 20,000 GitHub stars and both ISO 9001 and ISO 27001 certifications, it is a serious platform, not a weekend project.
主な特徴：
🤖 Real AI or automation? Real AI, and among the most convincing here. Teable's agent reasons about your request, builds structures, and runs live models inside fields. This is not a rules engine pretending to think.
Teable is the pick if you want the ceiling of an AI database and the floor of an open-source one. Nothing else on this list matches that combination at this price.
2. Airtable: The Most Powerful AI Agents, If You Can Afford Them
Airtable spent 2024 and 2025 doing a full “AI refound,” and the result is the most capable agent stack in the category. Omni is the conversational builder: describe an app and it spins up tables, interfaces, and automations in real time, and building with it does not cost credits.
Field Agents are the workhorses, running inside every record to analyze documents, search the web, generate images, translate content, and extract insights from transcripts, automatically and at scale. For a 10,000-row research task where you need the exact same prompt applied to every entry, this is genuinely impressive.
The catch is the invoice. Airtable is per-seat, and the jump from Team to Business is a 125 percent price increase per user. On top of that, AI actions consume credits, and a heavy document analysis can eat 500 to 1,500 credits in a single run.
Founded in 2012 and now valued around $11.7 billion after its Series F, Airtable is stable and enterprise-grade. It is also the most expensive way to get AI database work done here, and the credit meter adds real budget uncertainty.
主な特徴：
🤖 Real AI or automation? Real AI, and the deepest agent tooling in this roundup. Field Agents that run continuously across thousands of records are a legitimate step beyond simple autofill.
3. 概念： AI Database Living Inside Your Whole Workspace
概念's advantage is context. Its databases live in the same place as your docs, wikis, and projects, so its AI agents can pull from everything at once. Since Notion 3.0 in September 2025, the platform shifted from an assistant that suggests to an agent that executes, working autonomously for up to 20 minutes across hundreds of pages.
カスタムエージェント, launched in February 2026, run on schedules and triggers, so an agent can watch a database, qualify a new row, and notify your team without you lifting a finger. You can even pick your model, choosing between GPT-5.2, Claude Opus 4.5, and Gemini 3, or letting Auto decide.
For database work specifically, AI Autofill is the standout. Define a property like sentiment or category and Notion fills it for every row, including new ones, as a background process. The honest caveat is scale.
Notion databases start showing performance drag somewhere around 5,000 to 10,000 rows, which is fine for knowledge work and light operations but a problem if your data is genuinely large. It is the best AI database for teams that live in documents, and the wrong one for heavy structured data.
主な特徴：
🤖 Real AI or automation? Real AI, with genuine agentic execution. The マルチモデルアクセス and 20-minute autonomous runs are well beyond cosmetic AI.
4. スマートスイート： AI Work OS Built for Operations Teams
SmartSuite calls itself an AI-native Work Operating System, and for once the label fits. It combines a relational database with workflow orchestration, automation, permissions, and reporting, then layers AI Field Agents on top that summarize records, draft content, classify requests, and score risk with a written rationale.
All of it runs through a centralized AI コントロールセンター, which is a smart touch for teams that need governance over where AI touches their data. You can build tables, fields, and views from natural language prompts, and the platform ships with more than 40 field types and nine view types including Timeline, Map, and Chart.
Where it earns its ranking is operational depth. Teams have consolidated Airtable, Asana, Smartsheet, and a pile of spreadsheets into a single SmartSuite workspace, and one enterprise reportedly cut $450,000 a year by moving 300-plus Salesforce licenses over.
It is more affordable at scale than Airtable, though it carries a three-seat minimum on paid plans and a real learning curve. This is a platform for people who run processes, not for someone who wants a quick table.
主な特徴：
🤖 Real AI or automation? Real AI. The Field Agents produce reasoned output like risk scores with explanations, which is meaningfully more than template automation.
5. スタックビー: The Value Pick That Lets You Bring Your Own AI
Stackby is the sensible-money choice. It looks and feels like a spreadsheet, behaves like a relational database, and layers AI fields on top where you bring your own API key from OpenAI, Gemini, or Anthropic. That last part is quietly brilliant: instead of paying a marked-up credit rate, you plug in your own model and pay providers directly at cost.
Inside a field, the AI can generate content, categorize records, summarize, and analyze documents. The other differentiator is Stackby's ノーコード APIコネクタ, which pull live data straight into columns from services like YouTube, Ahrefs, Clearbit, and Hunter.io. Very few tools do column-level API enrichment this cleanly.
Stackby is trusted by more than 100,000 companies and is actively transforming into an AI-native app builder, so the roadmap points the right way. It offers eight views, 30-plus column types, and forms with conditional logic.
It is not the deepest agent on this list, and some templates feel thin, but for the price it delivers most of what Airtable does without the sting. If your budget is real and your needs are practical, this is the smart buy.
主な特徴：
🤖 Real AI or automation? Real AI, powered by whichever model you connect. Because you supply the key, the intelligence is exactly as strong as the LLM you choose.
6. ベースロー: The Open-Source AI Database You Can Actually Own
If data ownership is non-negotiable, Baserow is the answer. It is MIT-licensed at the core, genuinely open source, and self-hostable via Docker, Kubernetes, or a manual setup. On top of that foundation it has built a legitimate AI layer: an assistant called Kuma that helps you create structures and formulas, AI fields that run repeatable generation, summarization, classification, and analysis directly inside tables, and newer agent workflows.
The detail that separates it from every closed tool here is that self-hosted Baserow can connect directly to your own AI providers at the workspace level, including a local Ollama model for offline or air-gapped setups. Your data and your model can both stay on your infrastructure.
Baserow gives you the familiar spreadsheet grid, Excel-style formulas non-developers can actually read, and an application builder for 内部ツール and dashboards on top of your data. It is GDPR, HIPAA, and SOC 2 aligned, which matters for regulated teams.
The free self-hosted edition has no row caps. It trails Airtable on polish and ecosystem, and there is no native mobile app yet, but for open-source AI database work with real compliance posture, nothing else here comes close.
主な特徴：
🤖 Real AI or automation? Real AI, and unusually flexible about it. Because you configure the model, you can run frontier LLMs or a fully local one, which is rare in this category.
7. ヒューズベース： AI Database Wrapped in Client Portals
FuseBase, formerly Nimbus, took a different path to this list. It is less a raw database and more an AI-powered client collaboration platform, and that is exactly why service businesses love it.
It combines a solid table manager and knowledge base with branded client portals and, crucially, AI agents that do real work: summarizing meetings, assigning tasks, sending reminders, generating client-ready recaps, and executing workflows based on your standard operating procedures.
You can spin up an agent for Sales, Support, HR, or Finance in under a minute and deploy it inside a portal, in your browser via extension, or through an automation. It even supports the モデルコンテキストプロトコル for deeper integrations.
The rebuild added SOC 2 and HIPAA compliance, e-signatures, and transcription, and the company now serves more than 3,000 customers. The trade-off is focus. If you want a pure high-scale database, this is not it, and the AI features are still maturing according to recent reviews. But if your data problem is really a client problem, managing documents, onboarding, and communication in one branded space, FuseBase turns an AI database into a client-facing operating system.
主な特徴：
🤖 Real AI or automation? リアル AI agents, oriented toward client operations rather than data crunching. They act on your behalf, which is more than a chatbot, though the feature set is younger than the leaders here.
8. ノコDB: The AI-Ready Layer Over Your Existing SQL Database
NocoDB earns its spot on a philosophy the others do not share. Instead of asking you to migrate into yet another silo, it points at a database you already own. Connect a MySQL, PostgreSQL, MSSQL, SQLite, or MariaDB instance and within seconds you get a spreadsheet-style interface on top of your real schema, plus an auto-generated REST and GraphQL API and webhooks for every table.
Your data never leaves your infrastructure. With over 50,000 GitHub stars and production use at companies like Google, Walmart, and American Express, it is the most battle-tested open-source option for putting a friendly UI on serious data.
Honesty check, since this is an AI list: NocoDB's AI is the thinnest here. Its strength is connectivity and data ownership, not agents, and its native AI tooling is still emerging compared to the rest of this ranking.
It also switched from AGPL to a source-available Sustainable Use License at v0.301, so self-hosting for internal use is free but reselling it as a managed service requires a license. If your data already lives in SQL and you want an AI-ready, API-first interface over it, NocoDB is the right tool. If you want the AI to build the database, look higher up this list.
主な特徴：
🤖 Real AI or automation? 最軽量 AI in this roundup. NocoDB is included because it is the most popular open-source database interface and is adding AI, but today its intelligence layer trails every other tool here.
リアル AI vs Dressed-Up Automation: How to Tell the Difference
The word “AI” is doing a lot of heavy lifting on vendor landing pages in 2026. Here is a practical test you can run in ten minutes on any tool before you commit.
Ask it to build something from nothing. Type “create an inventory system with suppliers, stock levels, and reorder alerts” and watch what happens. A real AI database builds the tables, relations, and logic. A dressed-up automation asks you to pick a template. Teable, Airtable, Notion, and SmartSuite all pass this test convincingly. Weaker tools stall.
Then push the field-level AI. Feed it messy data, a folder of receipts or a column of raw customer feedback, and ask it to extract structured information. Genuine LLM fields will pull vendor names, totals, sentiment, and categories. Rule-based automation returns errors or empty cells the moment the input strays from the expected format.
Finally, check who owns the model. Tools that let you bring your own key (Stackby) or point at a local model (Baserow, self-hosted Teable) are giving you real, swappable intelligence. Tools that lock you into a fixed credit meter are betting you will not notice the markup. That single question separates the platforms that respect your budget from the ones that do not.
正しい選び方 AI Database for Your Team
You do not need all eight. You need the one that matches your actual constraint.
Most teams land on Teable for the core system and add one specialist tool around it. That is a $10 to $30 per month stack that covers the entire AI data workflow, and it beats paying enterprise rates for features you will not use.
よくある質問
何が最善の方法です AI database tool in 2026?
Teable is the best all-round AI database tool in 2026. It combines a talk-to-build AI agent, cell-level AI fields with 154 language models, PostgreSQL scale, an open-source self-hosted edition, and credits billed at cost with zero markup. Airtable has deeper agent tooling but costs far more, which is why Teable takes the top spot for most teams.
どの AI database tools are free?
Several offer real free tiers. Teable's free plan includes AI フィールド、 AI Chat, and app generation. Stackby is free for up to 5 users. Baserow and NocoDB both have free cloud plans plus free self-hosted editions. Airtable, Notion, and SmartSuite have free tiers too, though full AI access on Notion and SmartSuite usually requires a paid plan.
Do these tools use real AI or just automation?
The top platforms use genuine large language models. Teable, Airtable, Notion, SmartSuite, Stackby, Baserow, and FuseBase all run real LLMs that reason, generate, and extract. NocoDB is the exception on this list, with the thinnest AI layer. A quick test is to ask the tool to build a database from a plain-language prompt. Real AI builds it, while automation hands you a template.
どの AI database is best for large datasets?
Teable and Airtable handle large datasets best. Teable runs on PostgreSQL and manages millions of rows without slowdown, while Airtable scales to 500,000-plus records on higher tiers. Notion is the weakest at scale, showing performance drag around 5,000 to 10,000 rows, so it is better for knowledge work than heavy structured data.
Can I self-host an AI データベース？
Yes. Teable, Baserow, and NocoDB all offer self-hosting. Teable's Community Edition is free under AGPL with unlimited rows and lets you bring your own AI model. Baserow is MIT-licensed and can connect to a local Ollama model for offline use. NocoDB installs over your existing SQL database. Self-hosting gives you data ownership and removes per-seat cloud costs.
Is Teable better than Airtable?
For most teams, yes. Teable matches Airtable's AI database features, adds an open-source self-hosted option, scales on PostgreSQL, and prices its AI credits at cost with no markup. Airtable's Field Agents are more powerful and its ecosystem is more mature, but its per-seat pricing and credit costs climb quickly. Teable delivers the better value and freedom for the majority of use cases.
いくらですか AI database tools cost in 2026?
Entry pricing ranges from free to about $20 per user per month. Teable Pro is $10 per seat, Stackby Economy is around $5, and Baserow Premium is around €5. Airtable Team and Notion Business both sit at $20 per user per month for AI. Watch for credit-based AI billing on Airtable and Notion, which adds usage costs on top of the seat price.
何ですか AI database agent?
An AI database agent is a system that builds and operates a database through natural language. Instead of manually creating tables and writing formulas, you describe what you need and the agent builds the structure, enriches records, answers questions about the data, and automates the follow-up work. Teable pioneered the term, and Airtable's Omni and Notion's Agents are close counterparts.
評決
その AI database category matured fast, and in 2026 the gap between the leaders and the pretenders is wide. Airtable has the most powerful agents if you can absorb the cost. Notion is unbeatable if your work lives in documents. SmartSuite, Stackby, Baserow, FuseBase, and NocoDB each win a specific lane, from 運用ガバナンス to client portals to raw data ownership.
But for the widest range of teams, Teable is the one to start with. It gives you AI-native database power, open-source freedom, PostgreSQL scale, and pricing that does not punish you for using the AI you signed up for. Start on the free plan, build a real system in an afternoon, and upgrade only when you actually hit a limit. That is the honest path to an AI database that works, and it costs nothing to begin.
AiMojoのおすすめ:
ボーナス： 200ドルの「AI 登録すると「マスタリーツールキット」が無料になります！
