Do I need a separate data warehouse for my Azure Database for MySQL data?

No. Definite includes a built-in lakehouse, so you don't need to pay for a separate warehouse like Snowflake, BigQuery, or Redshift. Your Azure Database for MySQL data syncs into open Parquet storage and is queried by a DuckDB-powered engine for high-performance analytics. Definite handles encrypted, persistent storage behind the scenes with enterprise-grade security, automatic syncing, and backups. You get lightning-fast queries, built-in business intelligence tools, and SOC 2 compliant security, all without the overhead or complexity of running a separate warehouse.

Can I analyze my Azure Database for MySQL data with other data sources?

Yes. Definite lets you connect and analyze data across all your tools: app databases, CRMs, marketing automation, analytics, and customer support platforms. Our built-in Sync Engine supports 500+ data sources, with options for daily, hourly, or near real-time syncs. You can select metrics and dimensions from your Azure Database for MySQL data alongside other sources to explore insights, build dashboards, and share results (no SQL needed, unless you want to). Or simply ask Fi, our AI analyst, to find answers, uncover patterns, and instantly create charts and reports for you.

Can Definite connect Azure Database for MySQL data to tools like Python, SQL, Google Sheets, or Slack?

Yes. Definite integrates seamlessly with the tools you already use. You can run Python scripts for advanced analysis, query your data directly with SQL, or sync results to Google Sheets and Slack for easy sharing. Data can be exported in CSV, Excel, or JSON, accessed via the Metrics API, or embedded directly into your product or internal dashboards. Definite makes it simple to connect, automate, and share insights wherever your team works.

How does Definite's AI actually work?

Definite includes Fi, our AI data analyst that understands your business data and speaks your language. Fi can explore your connected sources, write SQL, and build charts or dashboards in minutes, turning plain-English questions into real analysis. Under the hood, Fi uses Definite's semantic models and query engine to interpret context, generate accurate queries, and explain results clearly. The result: faster insights, fewer bottlenecks, and analytics that finally deliver ROI.

Can I use Definite for free?

Yes. Definite offers a free plan for qualifying startups that includes core analytics, dashboards, and AI insights: everything you need to get started. You can upgrade anytime for more data sources, faster syncs, and advanced automations.

Definite runs as a private deployment in your own cloud (AWS, GCP, Azure, or anywhere with Kubernetes); you keep control of data, compute, and networking. Explore private deployment →

Explore with AI

← All connectors/Application Database

§ Connector

Azure MySQL

Analyze your Azure Database for MySQL data with AI today.

Build dashboards, automate reports, and ask questions in plain English — all from your Azure Database for MySQL data, no complex infrastructure to maintain.

Watch the demo →Try it free

Have multiple Azure Database for MySQL accounts? Analytics across multiple Azure Database for MySQL accounts →

Want it to watch your Azure Database for MySQL data and act on its own? Meet the Azure Database for MySQL agent →

§ Live with

§ What you get

Everything Azure Database for MySQL exposes, modeled and queryable.

Extracts data from Azure Database for MySQL (MySQL-compatible). Replicates user-selected tables and views via full-table or incremental (binlog/key-based) sync.

Standard on every Definite connector

Sync cadence

Hourly or faster

CDC

Native where supported

Auth

OAuth / API key

Row-level security

Yes

Tables & streams

3 objects

◆Table

User-selected database tables replicated via full-table or incremental sync (binlog CDC or key-based); the primary data extraction path for transactional and operational data.

general_data_storage

◆View

Database views accessible as read-only data sources; enables extraction of pre-joined or pre-aggregated datasets defined in the source database.

general_data_storage

◆Schema Catalog

Table and column metadata including data types, keys, and indexes; powers catalog discovery and schema-change detection for downstream consumers.

general_data_storage

Authentication

Authenticates with a database user and password over TLS (ssl-mode=REQUIRED), with a firewall rule allowing the connector's source IP.

Requirements

Requires an Azure Database for MySQL (Flexible Server) instance with a database user and firewall access.

Domainsgeneral_dataoperations