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Yes. MongoDB and MySQL can run on the same Linux server, and their documented default TCP ports do not conflict: MongoDB listens on 27017, while MySQL uses 3306. Running both successfully is mainly a capacity, isolation, security, and operations problem—not an installation incompatibility.
This guide explains how to install and verify both services, keep their resources and data separate, secure their network exposure, detect contention, and decide when separate servers are the safer design.
Why MongoDB and MySQL do not inherently conflict
A Linux server can run many database engines at once. Each service has its own process, configuration, data files, logs, users, and listening socket. A TCP port can be owned by only one process on a given IP address, but MongoDB and MySQL use different defaults.
| Database | Typical service process | Documented default TCP port | Local connection example |
|---|---|---|---|
| MongoDB | mongod |
27017 |
mongosh --host 127.0.0.1 --port 27017 |
| MySQL | mysqld (package naming can vary) |
3306 |
mysql -h 127.0.0.1 -P 3306 -u username -p |
MongoDB’s Ubuntu installation documentation identifies the vendor-maintained mongodb-org packages and documents the default listener at port 27017. Its Red Hat-family instructions also cover service management and port verification: MongoDB Community Edition on Ubuntu and MongoDB Community Edition on Red Hat or CentOS. Oracle’s MySQL documentation identifies 3306 as the default TCP/IP port and describes startup through systemd or the MySQL startup script: mysql.server — MySQL Server Startup Script.
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A conflict appears only when you deliberately configure both services to use the same address and port, or when a third process already occupies one of the required ports. Changing MongoDB or MySQL to a custom port is fine, provided every client, firewall rule, monitoring check, and backup tool uses the new value.
What you must decide before installing
Confirm distribution and release support
Use the vendor-supported package path for the exact Linux distribution, release, and CPU architecture. MongoDB’s version 8.0 documentation lists supported Ubuntu and Red Hat-family combinations; support is release-specific, so check the applicable page immediately before deployment rather than assuming that every derivative distribution is covered.
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Install MongoDB from MongoDB’s official repository or package instructions for your release. Install MySQL from the package source supported for that same release. Mixing an unofficial database package with a vendor repository can create incompatible files, service definitions, or upgrade behavior.
Inventory the combined workload
Write down the expected peak, not just the average, for both applications:
- Concurrent connections and request bursts.
- Read/write mix and the latency target for each workload.
- Current and projected data volume, including indexes, temporary files, binary logs, and replication or journal-related space.
- Backup duration and the time during which backups may compete with production traffic.
- CPU, memory, storage capacity, and disk-latency observations from the existing server.
The official installation pages do not publish a universal RAM minimum, benchmark, or safe combined database-size threshold for co-locating MongoDB and MySQL. Treat sizing as an observation-and-load-testing exercise. A server that is comfortable for two small development databases may be unsuitable for two production systems with independent traffic peaks.
Install both databases without mixing their administration
1. Install MongoDB from its supported Linux packages
Follow the MongoDB instructions for your distribution and release, including repository configuration, package installation, and any required repository signing setup. The package creates the mongod service and the configuration and data locations expected by that distribution.
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Do not copy repository entries from a different Ubuntu or Red Hat release. A package that happens to install can still be unsupported or fail during a later upgrade.
2. Install MySQL using the supported package path
Use the MySQL package or repository instructions for the same Linux release. MySQL may register as mysqld or mysql, depending on the distribution and package family. Use the service name installed on your host when running systemd commands, and keep MySQL’s configuration and data locations under its own ownership and permissions.
3. Enable and start each service independently
On a systemd-based Linux host, enable and start MongoDB with the service name documented for the package:
sudo systemctl enable --now mongod
sudo systemctl status mongodFor MySQL, use the service name supplied by its package, for example:
sudo systemctl enable --now mysqld
sudo systemctl status mysqldIf your distribution registers the unit as mysql, substitute that name. MySQL also documents its startup script and systemd integration; do not create a second, hand-written startup mechanism that could launch an additional instance.
4. Verify listeners and local connections
Check which processes own the database ports:
sudo ss -ltnp | grep -E ':(27017|3306)b'You should see one listener for MongoDB on the configured address and port and one for MySQL on its configured address and port. Then test each engine separately with its client:
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mongosh --host 127.0.0.1 --port 27017
mysql -h 127.0.0.1 -P 3306 -u username -pA successful local connection proves that the process is running and reachable from the host; it does not prove that remote applications, authentication, backups, or failover procedures are correctly configured.
Keep files, identities, and maintenance paths separate
Co-location is safer when each database has a clearly separate administrative boundary.
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- Use the package-created MongoDB and MySQL data directories rather than pointing both services at a shared directory.
- Keep log files in their respective database logging paths, with independent rotation and retention policies.
- Do not make one database’s service account the owner of the other database’s files.
- Create separate operating-system and database credentials for administrators and applications. Grant each application access only to its own database objects.
- Schedule MongoDB and MySQL backups as distinct jobs with distinct destinations and retention policies.
- Reserve enough free space for temporary files, logs, binary logs, journal or recovery data, and a backup staging area. A full filesystem can take both services down even when their individual data directories look healthy.
Separate directories do not create performance isolation by themselves. Both engines still compete for the host’s CPU, memory, storage queues, and kernel resources.
Configure network exposure deliberately
Bind to the smallest required interface
If an application runs on the same server, prefer a loopback address such as 127.0.0.1 when the database does not need remote access. For an application on a private network, bind to the required private interface and keep the service off public interfaces unless there is a specific, protected reason to expose it.
Check the effective bind address and port in each service’s configuration rather than assuming the defaults. A service can be listening on a different port after a previous administrator changed it.
Apply firewall rules to both ports
Allow TCP 27017 and 3306 only from the application hosts, administration network, or other systems that genuinely need access. Do not open both ports to the entire internet as a shortcut for testing. If you use custom ports, document the mapping and update firewall, monitoring, client connection strings, and incident runbooks together.
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Use database authentication and encrypted transport where required
Enable the authentication and transport-security settings appropriate to your MongoDB and MySQL deployments, and verify them from a client that is not using an implicit local trust path. Network filtering is a second layer; it is not a replacement for database credentials, least privilege, or encrypted connections.
How to size one host when both databases share it
Memory pressure
MongoDB and MySQL can both consume memory for working data, indexes, connections, internal buffers, and the operating system’s cache. The important measurement is the combined peak, including application processes and backup utilities. Watch available memory, swap activity, and kernel out-of-memory events during realistic traffic and backup runs.
There is no defensible single “RAM required” number from the cited vendor documentation. Start with measured usage, leave headroom for bursts and maintenance, and repeat the measurement after data growth or configuration changes. If either service regularly drives the host into swap or causes the operating system to terminate processes, reduce the workload or move one database to another host.
CPU contention
Index builds, aggregation or reporting queries, schema changes, compaction or recovery work, encryption, and backups can create short CPU spikes. Compare per-process CPU usage with application latency, not just the server’s daily average. A host that looks idle most of the day can still be undersized if both databases peak at the same time.
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Storage capacity and latency
Capacity must cover active data, indexes, logs, temporary files, recovery space, and local backup staging. Throughput alone is not enough: simultaneous random reads, writes, flushes, and backup scans can increase latency for both databases. Monitor disk latency and queue depth while each service is busy, and test the backup window as a production workload.
Connection and process limits
Account for database connections, application workers, monitoring agents, shell sessions, and backup processes in the host’s file-descriptor and process limits. Raising a database connection limit without checking memory and operating-system limits can replace connection errors with instability.
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Backups and recovery on a shared server
Back up MongoDB and MySQL independently using methods appropriate to each engine. Store copies on storage that is not the same filesystem as the live database whenever possible. A local copy alone does not protect against filesystem corruption, host failure, or an administrator mistake.
Give each backup job a defined schedule, retention period, encryption policy, and restore procedure. Measure how long a restore takes and how much CPU, memory, and I/O it consumes. Stagger heavy backup jobs if they otherwise overlap with both databases’ peak traffic. A backup that completes successfully but causes unacceptable production latency is still an operational problem.
Common failure modes and practical fixes
“Address already in use” during startup
Inspect ownership before changing configuration:
sudo ss -ltnp | grep -E ':(27017|3306)b'Stop the unexpected process if it is not required, or assign the database a documented unused port. Update every client and firewall rule before restarting.
The service starts and then exits
Read the unit’s journal and the database log:
sudo journalctl -u mongod --no-pager
sudo journalctl -u mysqld --no-pagerFor MySQL installations using the mysql unit, substitute that unit name. Look for invalid configuration syntax, wrong file ownership, an unavailable data directory, insufficient disk space, or a port conflict. Correct the underlying issue and restart one service at a time.
Remote clients cannot connect
Confirm the process is listening on the intended interface, then check the host firewall and any network firewall between client and server. A local connection to 127.0.0.1 does not test remote routing. Also verify that the client uses the configured port rather than assuming 27017 or 3306.
Both applications become slow together
Correlate application latency with memory pressure, CPU saturation, disk latency, and backup activity. If the slowdown occurs only when one database performs maintenance or a backup runs, reschedule or throttle that work. If either workload regularly exhausts host resources, co-location has reached its practical limit.
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Check database logs, binary logs, temporary files, backup staging, and log-rotation status. Free space safely according to each database’s retention and recovery procedures; never delete active database files or logs blindly.
One server or separate servers?
Use one server when the combined workload is modest, the cost and simplicity benefits matter, and you can monitor and restore both services confidently. Use separate virtual machines or physical servers when predictable latency, fault isolation, or independent maintenance is more important than minimizing host count.
| Decision factor | One Linux server | Separate hosts |
|---|---|---|
| Cost and administration | Lower host cost and fewer systems to maintain | More infrastructure and separate operating-system maintenance |
| Failure domain | A host, kernel, storage, or power failure can affect both databases | A failure on one host is less likely to stop the other database |
| Performance isolation | CPU, memory, and storage contention are possible | Workloads have stronger resource isolation |
| Backup and maintenance windows | Jobs and upgrades compete for the same resources | Schedules can be planned independently |
| Security boundary | Both services share the host’s kernel and base operating system | Network and host boundaries provide additional separation |
Before choosing, compare total cost, peak memory demand, storage I/O contention, failure-domain requirements, backup and restore windows, security boundaries, and the team’s ability to operate two hosts. There is no universal database-size cutoff that determines the answer.
Quick Recap
Production readiness checklist
- The exact Linux distribution, release, architecture, MongoDB version, and MySQL version are supported by their vendors.
- MongoDB and MySQL were installed from their supported package or repository paths.
- Each service is enabled, starts after reboot, and has a healthy status.
- Listeners are on the intended addresses and unique ports.
- Firewall rules allow only required sources to reach TCP 27017 and 3306, or the documented custom ports.
- Data directories, logs, service accounts, credentials, and backup jobs are separate.
- Memory pressure, CPU saturation, disk capacity, disk latency, and backup impact are monitored.
- Backups are stored separately and a restore has been tested for both databases.
- There is a documented trigger for moving one database to another host, such as recurring resource exhaustion or unacceptable latency.
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