As a developer or data analyst, your data storage solution can make or break your application or analysis. SQLite and PostgreSQL are popular open-source options, but they have key differences you should understand before deciding between them.
This comprehensive guide will compare SQLite and PostgreSQL across critical factors like performance, scalability, features, use cases, and more. You’ll learn the pros and cons of each database and how to determine which one best fits your specific needs.
By the end, you’ll be able to choose the right database for your next project confidently. Let’s dive in!
What's in this article
A Quick Primer on SQLite and PostgreSQL
Before we compare SQLite and PostgreSQL directly, let’s briefly introduce both databases.
What is SQLite?
SQLite is a widely used open-source relational database that stores data in single, cross-platform disk files. It implements most SQL92 standard features but omits some, like Triggers, Check Constraints, and Partial Indexes.
Some key facts about SQLite:
- Serverless – SQLite is not a separate process or server, so it’s zero-configuration. The database file contains everything needed, including the database itself, tables, indices, and data.
- Self-contained – The entire database is stored in a single cross-platform file on the host machine. This makes SQLite databases highly portable and easy to manage, transfer, and backup.
- No separate server process – As it’s serverless, SQLite has a simple API for languages to connect and interact with the data. There’s no client/server communication overhead.
- Wide language/platform support – SQLite works with most programming languages and platforms like Windows, Linux, macOS, Android, iOS, etc. It’s integrated into Android, iOS, macOS, and many other platforms.
- ACID-compliant – SQLite transactions adhere to Atomicity, Consistency, Isolation, and Durability principles, so data integrity is ensured.
- Simple admin – No complex installation, configuration, or hosting required. You interact with the database file directly.
- Limited concurrency – As it uses file locking for write access, concurrent writes will queue, and only one write can happen simultaneously. Concurrent reads can still happen freely.
SQLite works great as an embedded database for desktop/mobile apps, websites, smart devices, and more. It offers a simple serverless SQL database that requires minimal setup and maintenance.
What is PostgreSQL?
PostgreSQL, also known as Postgres, is a powerful open-source object-relational database management system (ORDBMS). It offers enterprise-class features comparable to commercial databases like Oracle or SQL Server.
Some key facts about PostgreSQL:
- Full-featured RDBMS – PostgreSQL supports complex SQL queries, transactions, foreign keys, joins, views, triggers, stored procedures, and more. It complies closely with SQL standards and offers many advanced features.
- Client/server architecture – Postgres uses a server process to manage the database, and clients connect to it. This enables multiple concurrent client connections.
- High extensibility – PostgreSQL offers extensive extensibility via custom data types, functions, operators, aggregates, indexes, etc. There is also a large ecosystem of third-party extensions.
- High performance – PostgreSQL offers excellent performance via advanced indexing, query planning, optimization, parallelization, and more. Workloads can scale across multiple cores and servers.
- High scalability – It can handle large datasets and high transaction volumes. PostgreSQL supports horizontal scalability across servers using replication, clustering, partitioning, and other methods.
- ACID compliance – Transactions adhere to atomicity, consistency, isolation, durability principles like SQLite.
PostgreSQL works great as a primary database for web/mobile apps, analytics, enterprises, SaaS apps, and other demanding workloads. It’s production-ready and capable of handling complex data at scale.
Now that we’ve provided a brief overview of both SQLite and PostgreSQL let’s compare them across several key factors:
SQLite vs PostgreSQL: Key Factor Comparisons
|Performance||Good for low/medium workloads||Excellent for heavy workloads|
|Scalability||Limited (single server)||Excellent (clusters)|
|SQL Support||Subset of features||Extensive advanced features|
|Administration||Simple, lightweight||Sophisticated, advanced|
|Use Cases||Embedded/local/mobile databases||Enterprise/cloud/web server applications|
|When to Use||Local/offline applications, simple needs||Multi-user applications, complex needs, large scale|
SQLite vs PostgreSQL – Performance
SQLite offers respectable performance for embedded/local workloads. It uses disk-based storage, so performance is limited by disk I/O speeds. The serverless architecture also prevents excessive resource usage.
Read performance is generally fast, especially with proper indexes. However, write performance can suffer due to file locking and serial operation. SQLite only allows one write operation at a time, so concurrent write operations will get queued.
PostgreSQL provides excellent performance thanks to its advanced indexing, query optimization/planning, parallelization, caching mechanisms, and multi-core/cluster scaling capabilities. It’s designed for performance on server-based workloads.
PostgreSQL also minimizes disk I/O with techniques like buffering. Workloads can utilize multiple CPU cores in parallel for faster processing. The client/server architecture prevents file-locking issues with concurrent writes.
PostgreSQL has much higher performance potential than SQLite for server, web, and other demanding workloads involving larger datasets, complex queries, and high concurrency.
SQLite vs PostgreSQL – Scalability
SQLite has limited scalability since it relies on a single disk file. The database size limit depends on the filesystem but is generally less than 140 TB. SQLite best suits smaller local databases up to 100 GB in size.
There is minimal concurrency due to the serialized write locking. SQLite works for low to moderate-traffic applications accessed by a few concurrent users/processes.
PostgreSQL scales very well across multiple dimensions:
- Storage capacity via tablespaces
- Complexity via materialized views
- Concurrency via connection pooling
- Read performance via replication
- Write performance via partitioning or sharding
PostgreSQL supports horizontal scalability across multiple servers using features like replication, clustering, partitioning, and sharding. It can handle high-traffic applications with 100s to 1000s of concurrent users. Database sizes routinely reach 100s of TB to PB scale.
PostgreSQL has much higher scalability potential than SQLite regarding storage size, complexity, concurrency, and workload volume. It’s designed to scale up and scale out gracefully.
SQLite vs PostgreSQL – Features
SQLite provides a decent subset of SQL capabilities but omits advanced SQL features like partial indexes, check constraints, triggers, and ACID compliance. Partial and expression indexes are not supported.
It supports primary, foreign, joins, views, and transactions – sufficient for many use cases. But the feature set is simpler compared to full enterprise RDBMS like PostgreSQL.
PostgreSQL offers an extensive feature set on par with Oracle and SQL Server. Key capabilities include:
- Complex SQL support including triggers, stored procedures, recursive queries, etc.
- Advanced index types like partial, expression, clustered, covering indexes, etc.
- Sophisticated transaction support with savepoints
- Multi-version concurrency control (MVCC) for isolation
- Advanced data types like arrays, JSON/XML, geometric, and custom types
- Table inheritance, table partitioning, materialized views
- Foreign data wrappers to access external data sources
- Replication, clustering, connection pooling, and other enterprise features
PostgreSQL supports comprehensive SQL capabilities and many advanced server features suitable for mission-critical enterprise systems. It’s one of the most full-featured open source RDBMS available.
PostgreSQL provides far more advanced database features and capabilities compared to SQLite. It offers extensive flexibility suitable for demanding workloads.
SQLite vs PostgreSQL – Administration
SQLite databases are self-contained single files, so administration is very simple. There is no separate database server process. You interact with the SQLite database file directly using a simple set of command-line administration tools.
Some administrative tasks like altering tables, adding indices, importing/exporting data can be done using built-in SQL commands. Backup involves simply copying the database file.
SQLite offers minimal, zero-configuration administration suitable for embedded databases. It does not aim to provide sophisticated administration tools.
PostgreSQL has advanced administrative capabilities suitable for enterprise database servers. This includes:
- Sophisticated command-line tools like pgAdmin, psql, pg_dump, pg_restore etc.
- Graphical admin tools like pgAdmin
- Monitoring via admin views and statistics collectors
- Automated vacuuming, analyzation, logging, backups, etc.
- Fine-grained access control and security management
- Streaming replication setup for high-availability
- Load balancing, failover management for clusters
- Extensive logging for auditing and debugging
Some many third-party graphical tools and IDEs simplify PostgreSQL administration. PostgreSQL offers professional-grade database administration suitable for production environments.
SQLite vs PostgreSQL – Use Cases
Given their distinct architectures and capabilities, SQLite and PostgreSQL are suited for different use cases:
SQLite works great as an embedded database for local/mobile apps, websites, smart devices, browsers, etc., where data needs to be stored locally. Some examples:
- Local data storage for desktop apps, mobile apps, browsers, smart devices, etc.
- Embedded database for websites/web apps (with low to moderate traffic)
- Storing user settings, cache, and other app metadata
- Simple analysis/prototyping on local data
- Basic database functionality for products requiring local data management
PostgreSQL excels as a server-based relational database for transactional or analytical workloads at any scale. Some examples:
- Primary database for SaaS, cloud/web apps, and web services
- Operational store for enterprise applications like ERP, CRM, and business apps
- Analytics backend for business intelligence and data warehousing
- High-traffic web/mobile apps and multi-tenant SaaS apps
- Critical applications where stability, performance, and scalability are paramount
SQLite is best for simple local/embedded databases, while PostgreSQL is ideal for robust server applications and enterprise data management.
When to Use SQLite vs PostgreSQL
Based on their capabilities and typical use cases, here are some guidelines on when to choose SQLite or PostgreSQL:
Prefer SQLite when you need:
- A simple, lightweight embedded database for a desktop/mobile app
- Low-maintenance data storage for a device or product
- Basic local data management with simple SQL
- A portable, serverless database file to bundle with an app
Prefer PostgreSQL when you need:
- A highly stable and feature-rich open-source RDBMS
- Centralized data storage for multi-user server applications
- To scale up beyond a single machine’s storage or compute limits
- Enterprise-grade DB for high-traffic transactional/analytical apps
- A database that can seamlessly scale up and scale out
For web/server applications, PostgreSQL should generally be preferred over SQLite unless there are specific low traffic, simple data, or ease of development reasons to use SQLite.
Example Usage Scenario: Web Analytics Platform
To make this choice more concrete, let’s walk through an example.
Your platform must ingest and process billions of monthly events from thousands of customer websites in real-time. The data will generate reports, visualize trends, export large result sets, and more.
In this scenario, PostgreSQL is the better database choice over SQLite because:
- Huge volumes of writes and reads need to be handled with low-latency
- Analytical queries will be complex and resource-intensive
- Data from multiple sources needs centralized storage and processing
- Customer base and data volumes will grow substantially over time
- High availability and uptime are critical for a cloud SaaS service.
SQLite would not realistically work here – the serverless architecture can’t handle high write concurrency, plus analyzing large multi-tenant data is slow. There’s no opportunity for scaling out, replication, etc.
PostgreSQL can ingest streaming data efficiently, run-heavy analytical workloads in parallel, scale-out across multiple servers, and provide enterprise-grade uptime. Choosing PostgreSQL will enable the building of a robust and scalable analytics platform.
This example illustrates when PostgreSQL is the clear choice over SQLite based on the use case requirements and benefits of PostgreSQL’s capabilities.
To summarize, here are some key points to help you choose between SQLite and PostgreSQL:
- SQLite is simple, serverless, and lightweight. It works great for embedded and local databases.
- PostgreSQL is advanced, robust, and scalable. It’s suitable for enterprise-grade web/cloud apps.
- Evaluate performance needs – PostgreSQL has much higher capabilities.
- Assess scalability needs – PostgreSQL can handle huge data volumes.
- Compare required features – PostgreSQL offers many more advanced SQL capabilities.
- Consider admin needs – PostgreSQL has sophisticated tools and automation.
- Identify use case fit – SQLite for simple local DBs, PostgreSQL for server apps.
- For web/cloud apps, PostgreSQL is usually the best fit for web/cloud apps unless a SQLite benefit like simplicity and portability is critical.
By taking this structured approach to compare the databases, you can make an informed choice based on your specific application requirements rather than just gut instinct or prior familiarity.
SQLite and PostgreSQL are great open-source databases but target different use cases. Now you have an in-depth understanding of how they compare and when to choose each one. Apply these insights to your next project to pick the database that best fits your needs!