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Replace 90% of your SaaS stack with PostgreSQL.
Implement semantic search with PGVector and pgai, enabling users to find information based on meaning, not just keywords.
Leverage PostgreSQL's TS Vector type and GIN indexes for efficient full-text search, eliminating the need for external tools like Algolia or Elasticsearch.
Use the PG GraphQL extension to automatically generate a GraphQL API from your database schema, simplifying data access for various clients.
Keep your applications dynamic with Electric SQL, which provides a seamless sync layer between your database and front end for real-time updates.
Roll your own authentication system with PG Crypto and PG JWT, ensuring secure user access and data protection without relying on paid SaaS solutions.
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Not always. While PostgreSQL offers powerful capabilities, it's crucial to evaluate whether it's the right tool for the job. Consider factors like scalability, maintenance overhead, and specific feature requirements before making a decision.
While PGVector is suitable for many AI applications, it might not match the performance and scalability of specialized vector databases for extremely large datasets or complex queries. Consider your specific performance needs.
Electric SQL distinguishes itself by acting as a sync layer between your PostgreSQL database and front-end, simplifying the process of building real-time applications without the complexities of WebSockets or custom data fetching code. Other solutions might offer different architectures or features, so it's important to evaluate your specific requirements.
Yes, implementing your own authentication requires careful attention to security best practices. Ensure you use strong password hashing algorithms, generate salts, and implement row-level security to protect your data. Regularly review and update your security measures to address potential vulnerabilities.
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