Do I need a separate data warehouse for my Amazon Aurora 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 Amazon Aurora 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 Amazon Aurora 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 Amazon Aurora 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 Amazon Aurora 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. Request a demo →

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← All connectors/Application Database

§ Connector

Aurora

Analyze your Amazon Aurora data with AI today.

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§ Live with

§ What you get

Everything Amazon Aurora exposes, modeled and queryable.

Extracts data from Amazon Aurora (PostgreSQL-compatible). Replicates user-selected tables and views via full-table or incremental (log-based/key-based) sync, enabling analytics over any schema without manual ETL.

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 (log-based 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, primary keys, and nullable flags; powers catalog discovery and schema-change detection for downstream consumers.

general_data_storage

Authentication

Authenticates to your Aurora cluster endpoint with a database user and password, over SSL. Aurora MySQL clusters connect through the generic MySQL connector.

Requirements

Requires an Amazon Aurora cluster (PostgreSQL- or MySQL-compatible) with a database user.

Domainsgeneral_dataoperations

§ How it works