Sales, investment, and go-to-market teams all need to know the same basic thing at roughly the same moments: which companies just raised money, got acquired, or hired a new decision-maker — because those events are exactly when a company is most likely to buy something, sell itself, or need a new vendor relationship. Building and maintaining a database to track that yourself across tens of thousands of companies is a serious data engineering project on its own. Datahyena sells that database as an API: over 65,000 resolved companies and 6,000+ deduplicated investors, with funding, acquisition, and executive-move data updated within hours of an announcement and sourced with citations so you can verify where it came from. The API supports both request-based queries and webhook streaming for real-time event notifications, plus native MCP protocol support for plugging directly into AI agent workflows. A single "company timeline" endpoint combines all three event types (funding, M&A, executive moves) for one company, and rate limits scale from 20 to 120 requests/minute depending on plan.
| # | Tool | Best for | Price |
|---|---|---|---|
| 1 | Équipes FinOps, DevOps, Finance IT et direction d'entreprise | — | |
| 2 | Équipes data engineering et governance, entreprises moyennes à grandes | — | |
| 3 | Développeurs et éditeurs SaaS embarquant de l'analytique dans leurs produits, y compris secteurs régulés | — | |
| 4 | Ingénieurs données, responsables FinOps/observabilité cloud, directeurs data en entreprise | — | |
| 5 | Équipes produit SaaS voulant réduire les coûts d'infrastructure analytics | — | |
| 6 | Équipes data et business utilisant des data warehouses cloud, cherchant du self-service analytics gouverné | — | |
| 7 | Data engineers et analytics engineers utilisant Python, Jupyter et orchestrateurs de données | — | |
| 8 | Entreprises moyennes à grandes (software, finance, santé, e-commerce) | — | |
| 9 | Équipes développement, product et data cherchant à embarquer des analytics dans leur produit | — | |
| 10 | Organisations financières, santé, télécom et secteur public avec exigences de résidence des données | — | |
| 11 | Startups, PME et équipes financières/RevOps sans data engineer dédié | — | |
| 12 | Dirigeants, analystes métier, agences et équipes SaaS/marketing cherchant à centraliser leurs KPIs | — |
A cloud cost management platform that gives finance, DevOps, and leadership a shared, accurate picture of where cloud money is actually going — down to 100% of costs allocated to teams or features — instead of finance and engineering arguing over spreadsh
A data quality platform built around 'data contracts' — explicit, collaborative agreements about what a dataset should look like — with AI that detects, explains, and can automatically fix anomalies when they break.
An established embedded analytics platform that lets software companies build dashboards and AI-generated insights directly into their own applications, with a 7-day free trial and full enterprise support for regulated industries.
An AI agent that watches your Snowflake, BigQuery, or Databricks bill and your data quality at the same time, flagging wasted spend and broken pipelines before they become a surprise invoice or a bad dashboard.
An embedded analytics platform built for SaaS companies that want to give their customers dashboards and self-service reporting inside the product, priced as a flat annual fee instead of per-seat or per-query.
A business intelligence platform that lets you explore data through chat, dashboards, raw SQL, or a spreadsheet-like interface — all pointed at the same governed set of metrics — and can be embedded directly into your own product.
The most widely used open-source tool for writing data quality checks in Python — you define what your data should look like as code, and it validates every pipeline run against those expectations automatically.
An AI-enabled analytics platform for embedding dashboards and AI-assisted insights into other software products, priced per workspace rather than per user, with a free-to-start Professional tier.
A toolkit for adding real analytics dashboards inside your own product — as a native web component, not a clunky iframe — so your customers get charts and self-service reports without you building a BI engine from scratch.
A data quality and observability tool that runs its checks directly inside your database instead of copying data out to a separate system, with pricing based on the number of tables you actually monitor rather than a flat platform fee.
An all-in-one data platform that replaces a Fivetran + Snowflake + dbt + Looker stack with a single tool for ingesting, storing, and querying business data, plus an AI analyst that answers questions in plain English.
A business dashboard tool that pulls numbers from 130+ apps (Google Analytics, Stripe, HubSpot, Facebook Ads...) into one screen, with an AI assistant that answers questions about your metrics in plain English.
