PostgreSQL vs. SQLite in 2025: When to Use Each

Choosing between PostgreSQL and SQLite in 2025 is less about which database is “better” and more about which one is the right fit for your workload, team, and deployment model. Both are mature, ACID-compliant relational databases with robust SQL support. They differ primarily in architecture, concurrency, operational complexity, and ecosystem.

This guide gives you a pragmatic, current perspective so you can decide with confidence—and switch later if needed.

Quick answer

• Choose SQLite when you need a zero-ops, embedded, single-file database with excellent read performance, simple deployment, and modest write concurrency.
• Choose PostgreSQL when you need multi-user concurrency at scale, advanced SQL features and extensions, strong security and governance, and built-in replication/HA.

What fundamentally differs

• Architecture
  • SQLite: Embedded, in-process library. Data is a single file on disk. No server to run or manage.
  • PostgreSQL: Client–server RDBMS. Separate process, sockets, roles, and network access.
• Concurrency model
  • SQLite: Many readers, single writer. WAL mode improves read concurrency but still one writer at a time.
  • PostgreSQL: Designed for high concurrency with many readers and many writers.
• Operations
  • SQLite: Ship the database file with your app. Backups are file copies or the online backup API. Replication and failover rely on external tools or hosted offerings.
  • PostgreSQL: Requires instance management. Offers built-in streaming and logical replication, point-in-time recovery, roles and permissions, and rich observability.
• Ecosystem and extensibility
  • SQLite: Core features plus built-in extensions (FTS5, JSON functions, R-Tree). Third-party extensions exist but are less standardized.
  • PostgreSQL: Deep extension ecosystem (PostGIS, pgvector, Citus, TimescaleDB, and more), procedural languages, and mature tooling across clouds.

Where SQLite shines in 2025

• Local-first, edge, and offline-capable apps
  • Perfect for desktop, mobile, IoT, and “edge” runtimes.
  • Excellent fit for Cloudflare D1, Turso/libSQL, and similar platforms that push data close to users.
• Simplicity and zero-ops
  • No server process, no provisioning, minimal moving parts.
  • Database lives with your app; easy to bundle, version, and test.
• Read-heavy workloads with modest write rates
  • WAL mode gives fast, concurrent reads with a single writer.
  • Very low latency due to in-process execution.
• Small to medium datasets
  • Tens of GBs are common and practical; far beyond that, consider your I/O pattern, backups, and maintenance story.
• Testing, prototyping, and developer ergonomics
  • Spin up instantly. Easy migrations. Great for CI and local dev.
• Cost
  • No server costs. Cloud/edge hosting for SQLite is typically inexpensive.

Where PostgreSQL shines in 2025

• High write concurrency and multi-tenant SaaS
  • Handles many concurrent writers reliably at scale.
  • Connection pooling, advanced indexing, and query planning.
• Advanced SQL and analytics features
  • Materialized views, window functions, sophisticated indexing (partial, expression, BRIN, GIN/GiST), CTEs, and more.
  • Strong JSON and XML capabilities, geospatial with PostGIS, and vector search with pgvector.
• Security, governance, and isolation
  • Roles, grants, Row-Level Security, fine-grained permissions, and auditing patterns.
  • Networked access with TLS, managed secrets, and enterprise controls.
• Reliability, replication, and HA
  • Streaming and logical replication, failover, PITR, robust backup tooling.
  • Mature managed offerings: Neon (serverless), Supabase, RDS/Aurora, Crunchy Bridge, and others.
• Long-term growth and complex workloads
  • Scales well vertically; with extensions and sharding solutions, can scale horizontally.
  • Rich performance tuning and observability options.

Performance characteristics you should actually care about

• Latency
  • SQLite is extremely low-latency for single-process reads because there is no network hop.
  • PostgreSQL adds a network boundary but can still be very fast with pooling and proximity.
• Throughput
  • SQLite can be blazing on read-heavy workloads; write throughput is constrained by the single-writer model.
  • PostgreSQL scales read and write throughput with parallelism and concurrency.
• Query complexity
  • Both support complex SQL, but PostgreSQL’s planner, indexes, and extensions handle heavier, more varied workloads better.
• Storage and size
  • SQLite’s file can grow large, but operational friction grows with it (backups, sync, compaction).
  • PostgreSQL is built for large datasets and long-lived production growth.

Feature comparison that influences real deployments

• Transactions and integrity
  • Both are ACID. SQLite requires enabling foreign keys per connection in many setups; PostgreSQL enforces them by default.
  • SQLite supports CHECK constraints, triggers, partial indexes, and generated columns. STRICT tables provide stronger type checks if enabled.
• JSON and full-text search
  • SQLite: JSON functions (json1) and FTS5 built-in. Great for lightweight indexing and search.
  • PostgreSQL: Advanced JSONB operations with indexing, and powerful search via extensions; generally better for complex document-query workloads.
• Geospatial and vectors
  • PostgreSQL: PostGIS for geospatial; pgvector for embeddings and vector search.
  • SQLite: R-Tree and several third-party vector extensions exist; hosted edge offerings may bundle these, but maturity varies.
• Stored procedures and extensibility
  • PostgreSQL: Procedural languages (PL/pgSQL and others), rich extension ecosystem.
  • SQLite: Triggers and virtual tables; fewer enterprise-grade extension patterns.
• Security
  • PostgreSQL: Network auth, roles, RLS, auditing. Encryption in transit standard; at-rest via disk or cloud features.
  • SQLite: File-level security. Encryption requires add-ons (e.g., SQLCipher) or filesystem encryption.

Operational considerations in 2025

• Backups
  • SQLite: Copy the file or use the online backup API. Validate snapshot integrity and flush state. External tools can stream to object storage.
  • PostgreSQL: pg_dump for logical exports, physical backups for faster restore, WAL archiving for PITR, and managed service tooling.
• Replication and HA
  • SQLite: Not built-in. Use tools like Litestream/LiteFS or hosted products (e.g., Turso) for sync/replication.
  • PostgreSQL: Native streaming/logical replication, failover tooling, and widely used HA architectures.
• Observability
  • SQLite: Minimal runtime metrics; observability is app-centric.
  • PostgreSQL: Extensive metrics, EXPLAIN/ANALYZE, pg_stat views, extensions for tracing and insights.
• Hosting
  • SQLite: Embedded with your app; edge/database-as-a-library; Cloudflare D1 and Turso for managed/edge patterns.
  • PostgreSQL: Vast managed ecosystem; serverless options reduce ops while preserving full Postgres capabilities.

Common use cases and recommended pick

• Mobile, desktop, and offline-first apps
  • Pick SQLite. Sync to a server or cloud when online.
• Edge-rendered apps and low-latency APIs close to users
  • Pick SQLite (e.g., D1/Turso) or combine with a central Postgres for authoritative data.
• Internal tools, prototypes, and small single-tenant apps
  • Start with SQLite. Consider Postgres once concurrency or data size grows.
• Multi-tenant SaaS, transactional systems, marketplaces
  • Pick PostgreSQL for concurrency, data integrity, RLS, and migrations at scale.
• Analytics and mixed workloads
  • Pick PostgreSQL for planner sophistication, materialized views, and extensions.
• Geospatial, vector search, and complex indexing
  • Prefer PostgreSQL for maturity and ecosystem depth, unless your needs are modest and you’re at the edge.

A simple decision checklist

• Team wants zero-ops, embedded, and fast local reads → SQLite.
• You expect bursts of concurrent writes or many concurrent users → PostgreSQL.
• You need strong security, RLS, and multi-tenant isolation → PostgreSQL.
• You’re building an offline-capable or edge-first app → SQLite (possibly with a central Postgres for sync).
• You need advanced extensions (PostGIS, pgvector, Citus, TimescaleDB) → PostgreSQL.
• You want the lowest cost and simplest deployment for a small app → SQLite.

Starting with one and moving to the other

• Start with SQLite, plan for PostgreSQL later
  • Use a migration tool and an ORM that supports both dialects.
  • Enable and test foreign keys in SQLite.
  • Avoid vendor-specific SQL early; keep schemas portable.
  • Build a data access layer that hides connection details.
  • When migrating: run schema migrations on Postgres, bulk-load data, verify constraints, and switch connections per environment variable or config.
• Start with PostgreSQL, keep a SQLite dev mode
  • Use SQLite for local development and CI speed, and PostgreSQL in staging/production.
  • Keep migrations idempotent and dialect-aware.

Pitfalls to avoid

• Assuming SQLite will handle heavy multi-writer workloads. It often won’t without careful batching and architecture.
• Forgetting to enable foreign key enforcement in SQLite connections.
• Using SQLite on networked filesystems or shared volumes without understanding locking implications.
• Over-optimizing early for Postgres complexity when a simple embedded store would suffice.
• Relying on niche extensions that limit portability without a clear reason.

Costs and total ownership

• SQLite minimizes infrastructure cost and operational overhead. Complexity can grow when you add replication, sync, or global distribution.
• PostgreSQL has a higher baseline cost (server or managed service) but reduces architectural risk for multi-user write-heavy systems and offers built-in pathways to HA and scale.

Bottom line

• If your app is local-first, edge-deployed, or has modest concurrency, SQLite provides unmatched simplicity and speed with minimal ops.
• If your app is multi-user, write-heavy, security-sensitive, or needs advanced features and growth headroom, PostgreSQL is the safer long-term foundation.
• Many teams successfully combine both: SQLite at the edge for speed and resilience, PostgreSQL centrally for authority, analytics, and governance.

Choose the engine that aligns with your current constraints, and keep your schema and tooling portable so you can evolve as your product and traffic evolve.