arcodash
Ask in plain English or write SQL, build a dashboard, and get alerted when a number goes wrong, with AI explaining why. 19 connectors. 14 days free, no card, then from $59/month, unlimited seats.
Ask in plain English or write SQL, build a dashboard, and get alerted when a number goes wrong, with AI explaining why. 19 connectors. 14 days free, no card, then from $59/month, unlimited seats.
This page is designed to help you find out whether arcodash is good and if it is the right choice for you.
arcodash is BI and data observability in one SQL-first tool, with AI built into every step.
Ask, or write SQL. Ask a question in plain English and an AI agent drafts the SQL, runs a read-only preview, checks the result and retries until it holds up. You read and edit the final query before saving. It knows your data because arcodash builds an AI profile of each source: sample values, stats, relationships and table/column descriptions. Prefer typing SQL? The editor has schema autocomplete and version history.
Dashboards. Tables, line, bar, area, pie and scatter charts, counters and funnels on grid dashboards with parameters, auto-refresh and shareable links. AI can pick the chart for you.
Know when a number is wrong. Freshness, volume and validity checks, or a threshold on any query, alert you by Slack, email, Microsoft Teams, PagerDuty, webhook, Mattermost, Discord, Google Chat or Datadog. AI suggests which checks to add, baseline monitors learn what normal looks like so you don't pick thresholds, and every alert explains why it fired by naming the segment that moved.
Connectors. 19: PostgreSQL, MySQL, Snowflake, BigQuery, MongoDB, SQL Server, Redshift, ClickHouse, Elasticsearch, Databricks, CockroachDB, MariaDB, Prometheus, Amazon Athena, SQLite, InfluxDB, TiDB, JSON over HTTP and CSV, plus Query Results for joining across them.
Pricing. 14 days free, no card. Then $59/month on Team or $300/month on Org, unlimited seats on both.
AI features use your own Gemini, OpenAI or Anthropic key, so model usage is billed by your provider with no markup. Hosted service. Your data stays in your database. Built by a solo founder, so feedback goes straight to the person writing the code.
Listed in
AI text to SQL agent
Ask in plain English. The AI drafts SQL, runs a read-only preview, checks the result and retries, then hands you a query you can read and edit.
AI alert explanations
When a check fires, AI slices the data and names the segment that moved, right in the Slack, email or PagerDuty alert.
Data quality checks
Scheduled freshness, volume and validity checks on the same SQL you chart, alerting 9 destinations. AI suggests which checks to add.
Anomaly detection
Baseline monitors learn what normal looks like and flag outliers, so you don't have to pick thresholds.
SQL dashboards
Charts, counters and funnels on grid dashboards with parameters, auto-refresh and share links. 19 connectors.
Flat pricing
$59/month on Team or $300/month on Org, unlimited seats. 14 days free, no card.
AI runs through the whole loop, from question to alert. Ask in plain English and an AI agent writes the SQL, runs a read-only preview, checks the result and retries until it holds up. Then it watches the data: it suggests which data quality checks to add, learns what normal looks like so you don't set thresholds by hand, and when an alert fires it tells you why. It slices the data and names the segment that moved, right in the Slack, email or PagerDuty message. Dashboards and data checks live in one tool, on the same SQL.
Data analysts, analytics engineers and small data teams who own the dashboards the business relies on, plus the less-technical people who need numbers from the warehouse and would rather ask in plain English. Typically startups and mid-size companies on Postgres, Snowflake, BigQuery, ClickHouse or similar.
The connect, query, visualize, dashboard, alert workflow is one a lot of data teams know from older self-hosted query tools. I wanted to rebuild it for the AI era: you ask a question and get a query that actually ran, and the tool keeps an eye on the data itself, so it answers "can I trust this number?" and not only "what is the number?". When something breaks it should tell you why, not just that a check failed. The name comes from the arc: it connects the dots, and it bears load. I build arcodash as a solo founder.
Rust (Axum, Tokio, SeaORM), PostgreSQL, Redis, React with TypeScript (Vite, TanStack Query, Recharts, Tailwind), Astro for the website, hosted on Google Cloud behind Cloudflare. AI runs on Gemini, OpenAI or Anthropic models, with an agent loop streamed to the browser.
Most teams run one tool for dashboards, a second for data quality, and a chat assistant on the side that doesn't know their schema. arcodash is one tool: the AI builds a profile of each data source (sample values, relationships, table and column descriptions), so its SQL fits your actual data, and the same engine that draws the chart alerts you when the number is wrong. It's SQL-first, so every AI answer is a query you can read and edit. Bring your own Gemini, OpenAI or Anthropic key, and pricing is flat, not per seat: $59/month on Team or $300/month on Org, unlimited seats on both. 14 days free, no card.
We have collected here some useful links to help you find out if arcodash is good.
Check the traffic stats of arcodash on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
Check the "Domain Rating" of arcodash on Ahrefs. The domain rating is a measure of the strength of a website's backlink profile on a scale from 0 to 100. It shows the strength of arcodash's backlink profile compared to the other websites. In most cases a domain rating of 60+ is considered good and 70+ is considered very good.
Check the "Domain Authority" of arcodash on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
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