What Is PostgreSQL?
PostgreSQL (often called Postgres) is an advanced open-source relational database system with over 35 years of development. It’s known for reliability, data integrity, and extensibility, making it a popular choice for business applications from startups to enterprises.
Key characteristics:
- Open source (free to use)
- ACID compliant
- Highly extensible
- Standards compliant (SQL)
- Strong community support
- Cross-platform
PostgreSQL Features
Reliability
- ACID transactions
- Point-in-time recovery
- Replication options
- Crash recovery
Functionality
- Advanced SQL support
- JSON/JSONB for semi-structured data
- Full-text search
- Geospatial (PostGIS)
- Custom data types
Performance
- Query optimization
- Parallel queries
- Table partitioning
- Sophisticated indexing
Security
- Row-level security
- SSL encryption
- Authentication options
- Audit logging
PostgreSQL in Business
Common PostgreSQL use cases:
Application databases
- SaaS application backends
- E-commerce platforms
- Content management systems
Operational data stores
- Transaction processing
- Inventory management
- Order management
Analytics
- Reporting databases
- Data marts
- OLAP workloads (with extensions)
Integration hub
- Foreign data wrappers
- ETL staging area
- Data consolidation
PostgreSQL vs. Other Databases
| Aspect | PostgreSQL | MySQL | SQL Server |
|---|---|---|---|
| License | Open source | Open source (Oracle) | Commercial |
| Advanced SQL | Excellent | Good | Excellent |
| JSON support | Excellent | Good | Good |
| Extensions | Extensive | Limited | Microsoft only |
| Cost | Free | Free/paid | Paid |
| Community | Strong | Strong | Microsoft |
PostgreSQL for Finance
Finance teams encounter PostgreSQL in several contexts:
Source system databases
- Application data stores
- Operational databases
- Custom business systems
Reporting databases
- Replicas for reporting
- Data marts
- Analytical extracts
Data integration
- Staging for ETL
- Consolidation layer
- Cross-system queries
Accessing PostgreSQL Data
Direct SQL access:
- Query tools (pgAdmin, DBeaver)
- Requires SQL skills
- Full flexibility
BI tool connections:
- Tableau, Power BI, Looker
- Requires data modeling
- Visualization focused
Export to Excel:
- Manual exports
- No automation
- Quickly outdated
With Go Fig:
- Automated extraction
- Delivered to Excel
- Combined with other sources
- No SQL required
How Go Fig Connects to PostgreSQL
Go Fig integrates directly with PostgreSQL:
What Go Fig extracts:
- Tables and views
- Custom queries
- Joined datasets
- Historical data
Delivery options:
- Excel spreadsheets
- Dashboards
- Semantic layer
- Other destinations
Benefits:
- No SQL skills needed
- Scheduled refreshes
- Combined with ERP, CRM data
- AI-powered analysis
PostgreSQL Best Practices for Finance
- Use read replicas: Don’t query production directly
- Create views: Pre-define useful data sets
- Index appropriately: Speed up common queries
- Document schemas: Know what tables contain
- Secure access: Limit who can query what
- Monitor performance: Track query impact
PostgreSQL Hosting Options
Self-managed:
- On-premise servers
- Cloud VMs (EC2, Compute Engine)
- Full control, full responsibility
Managed services:
- Amazon RDS for PostgreSQL
- Azure Database for PostgreSQL
- Google Cloud SQL
- Heroku Postgres
Serverless:
- Amazon Aurora Serverless
- Neon
- PlanetScale (MySQL-compatible)