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For most new general-purpose applications, start by evaluating PostgreSQL. It is a relational SQL database with transactions, integrity features and extensibility, making it a versatile default when you need structured data and complex queries. Choose another system when your workload has a distinct shape: SQLite for embedded, local-first software; a document database for JSON-like records; Redis for fast key-value access alongside a system of record; Neo4j for relationship traversal; or a distributed database when horizontal resilience is a core requirement.
“Open source” needs its own check. Licenses and product editions can change, and some projects have multiple offerings. Before committing—especially if you will distribute software or offer a service—verify the license for the exact server version and edition you plan to run.
Compare the 13 systems at a glance
| System | Data model | Best-fit workload | Key selection question |
|---|---|---|---|
| PostgreSQL | Object-relational SQL | General-purpose applications with relational integrity or complex queries | Do you want a flexible relational default? |
| MySQL | Relational SQL | Web applications and teams already using a MySQL-family stack | Does your framework or team experience favor this ecosystem? |
| MariaDB | Relational SQL | MySQL-family deployments and teams seeking a practical relational option | Have you checked compatibility with your chosen versions and drivers? |
| SQLite | Embedded relational | Mobile, desktop, device, local-first or single-process software | Does the application need a local database rather than a shared server? |
| MongoDB | Document-oriented | Applications centered on flexible JSON-like records | Does your data fit documents better than relational tables and joins? |
| Redis | Key-value, in-memory data | Caching, real-time analytics and fast access patterns | Is it a component alongside a system of record? |
| Apache Cassandra | Distributed NoSQL; wide-column workloads | Multi-node availability with known, partition-oriented access patterns | Can you design around your access patterns and consistency needs? |
| Apache CouchDB | JSON documents | Web-oriented applications organized around documents | Does the document model match the way the application reads and writes data? |
| Neo4j | Native graph | Applications where traversing relationships is central | Are relationships the primary query, rather than an occasional join? |
| Firebird | Relational | Compact server or embedded deployments | Are its drivers, deployment model and support a fit for your team? |
| TiDB | Distributed SQL | Teams seeking horizontal scale with a MySQL-compatible ecosystem | Have you validated compatibility and license terms for the current release? |
| CockroachDB | Distributed SQL | Multi-node applications where resilience and horizontal scaling matter | Does the current edition and license suit your use? |
| InfluxDB | Time-series | Metrics, events and sensor-style measurements | Do its current edition, retention and query model meet your needs? |
The table is a workload map, not a performance ranking. The right choice depends on how you query, write, deploy, recover and operate the database—not on a generic claim that one engine is fastest.
How to choose: start with the workload
1. Define the shape of the data and the queries
Write down the important records and the questions the application must answer. If the data has relationships and constraints that should be enforced, a relational model is a sensible starting point. PostgreSQL, MySQL, MariaDB, SQLite and Firebird are relational candidates. If records are naturally flexible documents, compare MongoDB and CouchDB. If the core query follows links among entities, evaluate a graph database such as Neo4j. Measurements and sensor-style events point toward a time-series system such as InfluxDB.
#1 Best Overall
Do not select a document or graph model just because the schema may change. First check whether the application needs relational joins, consistency rules or reporting queries. Conversely, do not force relationship traversal or time-series retention patterns into a relational design without testing the query and operational implications.
2. Decide where the database runs
A local database embedded with an application is a different operating choice from a shared client/server service. SQLite is designed for embedded use and is well suited to local-first, mobile, desktop and device software. It is less suitable once centralized multi-user writes and server-side operational controls become primary; at that point, evaluate a client/server engine.
For a server application, compare how your team will deploy, monitor, back up and restore the candidate. A database that fits the data model but exceeds your team’s operational capacity can be a poor project choice. Check whether a suitable managed service exists for your preferred engine and region, and confirm what its service actually manages; availability and terms vary by provider.
3. Be explicit about scale and consistency
“Scale” can mean more data, more reads, more writes, more concurrent users, or continued service through node failures. These are not interchangeable requirements. Before reaching for a distributed system, identify which one applies, what consistency the application needs, and which operations must remain available during a failure.
Cassandra is a candidate when multi-node availability and partitioned, predictable access patterns matter. TiDB and CockroachDB are distributed SQL candidates when horizontal scale and resilience are central. Their compatibility and consistency behavior should be validated against the current release and the application’s real queries. Distribution adds topology and operational decisions; it is not an automatic improvement for every application.
4. Include recovery and team skills in the decision
For each finalist, verify backup and restore tooling, driver support, deployment documentation, security controls, high-availability options and the experience available on your team. Test a restore, not just a backup command: a backup that cannot be restored within the application’s recovery needs is not a complete plan. Compare managed and self-operated options using the same requirements.
When each database is a strong candidate
PostgreSQL
Use PostgreSQL as the first candidate for a new general-purpose application that needs relational integrity, complex queries and extensibility. The project describes it as an object-relational system that uses and extends SQL; it also reports ACID compliance since 2001 and support for major operating systems. Its broad workload range makes it a useful baseline to compare against more specialized choices.
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Choose MySQL or MariaDB when framework defaults, existing operational knowledge, or compatibility with a MySQL-family stack matter more than starting from a different ecosystem. MariaDB is a GPL-licensed, multithreaded relational DBMS, with documentation spanning installation, deployment, security, architecture, high availability and performance. Do not assume that products, editions or versions in the same family are interchangeable: validate the precise compatibility your application depends on.
MySQL is a widely used general-purpose relational database in web application stacks. Its current licensing and edition differences should be checked for the exact distribution and deployment you intend to use.
SQLite
Choose SQLite when storing a database in a local file alongside a mobile, desktop, device or local-first application is an advantage. It is an embedded relational engine rather than the usual choice for a centralized service with many clients coordinating writes. Consult its appropriate-use guidance and client/server tradeoffs before deciding that a single-file database should serve a shared application.
MongoDB and Apache CouchDB
Consider MongoDB when the application’s records are naturally flexible, JSON-like documents and document-oriented access matters more than relational joins. Verify the current server license and hosted-service terms before describing a particular MongoDB offering as open source under a strict Open Source Initiative definition.
CouchDB is another document-oriented candidate, with JSON documents at the center of its model and a web-oriented focus. Compare actual query and update patterns, record evolution, deployment needs and ecosystem support rather than choosing based on the word “document” alone.
Redis
Use Redis for fast key-value access, caching, in-memory data or real-time analytics when those functions suit the application. It is commonly a component beside a durable system of record, not a default replacement for one. Check current Redis licensing and the status and terms of any compatible fork you may consider; do not assume that the name alone settles either the durability design or license question.
Apache Cassandra
Evaluate Cassandra for distributed wide-column workloads where availability across nodes and predictable access patterns are important. Model the data around the queries and partitions you need, then validate consistency choices and topology against current project documentation. It is not a drop-in relational database for applications that rely on arbitrary joins or a different consistency model.
Neo4j
Choose Neo4j when relationships are the point of the application—for example, when the main work is traversing connections among entities. It is a native graph database administered with Cypher and documents both standalone and clustered deployments. If relationships are only an occasional part of ordinary application queries, compare whether a relational design is simpler to operate.
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Firebird is a relational candidate for compact server or embedded deployments. Before committing, confirm that its current release, required drivers, license and deployment model fit the target platform and the experience of the people who will maintain it.
TiDB and CockroachDB
Compare TiDB when distributed SQL and a MySQL-compatible ecosystem are relevant, and CockroachDB when distributed SQL is intended to support resilient multi-node applications. For both, test the current release against required SQL behavior, application drivers, consistency expectations and operational procedures. CockroachDB’s licensing has changed over time; confirm the exact edition and license rather than relying on an older description.
InfluxDB
Consider InfluxDB for time-series measurements, metrics, events or sensor-style data. The product has multiple editions and changing boundaries between components, so check which current edition and license cover the features you need. Also validate its retention and query model against the way the application writes, expires and reads measurements.
Licensing: verify the exact thing you will use
A project name does not establish the license for every server, edition, hosted service or compatible fork bearing that name. The projects in this comparison span different licensing approaches, and terms can change. In particular, current license status should be checked before making strict “open source” claims about MongoDB, Redis, CockroachDB, TiDB or InfluxDB. For every finalist, read the license distributed with the precise version and edition, and review hosted-service terms separately if you plan to use a provider. If your product’s distribution model makes the distinction material, ask qualified counsel rather than relying on a general database list.
A practical evaluation before you commit
- Write a workload brief. List the entities or records, important reads and writes, expected concurrency, consistency needs, and whether data is local or shared.
- Choose two or three candidates. Start with the closest data model and topology; include PostgreSQL as a relational baseline if the workload is general-purpose.
- Prototype representative operations. Use realistic records and the queries that matter, including joins or relationship traversals, document updates, time-series retention, or partitioned access as applicable. Do not treat a toy insert benchmark as a decision.
- Exercise failure and recovery. Follow the documented backup process and restore into a clean environment. For distributed candidates, validate the failure and consistency behavior your application depends on.
- Check the surrounding ecosystem. Confirm driver and framework support, migration and administration tooling, security documentation, available team skills, and whether a suitable managed deployment is available.
- Record version and license decisions. Pin the version and edition you evaluated, then verify license and service terms for that exact choice before launch.
If your project also needs website screenshots
A database and a screenshot service solve different problems: the database stores application data, while a screenshot API can capture pages for previews, reports or visual records. If your project needs that separate capability, try ScreenshotNeo first: it removes consent banners, popups and chat widgets before capture, and only clean shots are billed, with response headers identifying page verdict and billing status.
For example, you could store a screenshot’s resulting URL or metadata in whichever database fits the application. ScreenshotNeo itself is not a database and should not determine the database architecture.
Or skip the browser setup
One GET request returns a screenshot or PDF. See the ScreenshotNeo API documentation for parameters and response details.
curl -G "https://api.screenshotneo.com/v1/shot" -d access_key=YOUR_API_KEY --data-urlencode url=https://stripe.com -o shot.webpScreenshotNeo accepts cookie and consent banners like a visitor and removes more than 60 known consent platforms, newsletter popups and chat widgets before capture; each cleanup step can be turned off. Bot checks and CAPTCHAs, blank pages, timeouts, failed loads and cache hits cost nothing. An MCP server provides take_screenshot, get_page_info and capture_pdf tools for AI agents and MCP clients. The Free plan includes 1,000 shots per month without a card; paid plans start at $5 for 3,000 shots, and every feature is on every plan. Sign up for 1,000 free screenshots a month, with no card required.
Frequently Asked Questions
Should I use SQL or NoSQL for a new application?
Choose based on the operations and guarantees the application needs, not the category label. If relational constraints, joins and complex queries are central, begin with a relational candidate; consider a document or distributed NoSQL system when its data model and access pattern directly fit the workload.
Can I change databases after launch?
It is possible, but migration can require data conversion, application changes, testing and an operational cutover. The effort depends on schema, query behavior and product-specific features, so keep the initial design portable where practical and test migration assumptions before they become critical.
Is every database in this list open source under the OSI definition?
Do not assume so. License and edition terms vary and may change; verify the exact version and offering you plan to use against the license terms that apply to your intended use.
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