MariaDB vs Percona Server: Drop-in Replacement or Compatibility Trap?

What “drop-in replacement” really means (and why it bites)

For operational purposes, “drop-in replacement” only means this: your application connects, runs migrations, serves traffic, survives failover, and you can back it up and restore it under pressure. Not “it starts” and not “it passes the unit tests.”

MariaDB and Percona Server both wear the “MySQL-compatible” badge, but they’re compatible in different directions and at different layers:

• Protocol compatibility: clients can usually connect. “Usually” hides auth plugins and TLS nuances.
• SQL dialect compatibility: common SQL works, but edge cases (JSON, window functions in older versions, optimizer hints) can drift.
• Behavioral compatibility: same schema and query may return the same rows… with different performance and different locking.
• Operational compatibility: backup tooling, replication semantics, and system tables matter more than most teams admit.

If you’re swapping between MariaDB and Percona Server, the trap is assuming they’re both “just MySQL.” Percona Server tends to track upstream MySQL closely (because it is fundamentally MySQL with extras). MariaDB took its own forked path long ago and kept evolving the “MySQL” label while changing internals and features.

Joke #1: “Drop-in replacement” is like “hot swap” in a change request: it means you’ll be swapping it while it’s hot.

Here’s the stance that saves teams: treat a MariaDB ↔ Percona Server move as a major engine migration, not a minor patch. Plan it like you would plan PostgreSQL ↔ MySQL? No. But closer than you want to believe.

Lineage and historical context (the facts people forget)

Some short history, because it explains today’s compatibility landmines. These are not trivia; they predict how your upgrade/migration will behave.

1. MariaDB forked from MySQL in 2009 after concerns about Oracle’s acquisition of Sun Microsystems and stewardship of MySQL.
2. Percona Server started as a performance-focused distribution that stays close to upstream MySQL while adding instrumentation and enterprise-grade features.
3. MariaDB diverged intentionally: it kept MySQL client protocol compatibility but introduced its own features and storage engines (notably Aria) and its own optimizer work.
4. GTID is not “one GTID”: MariaDB GTID implementation differs from MySQL/Percona GTID, affecting failover tooling and mixed topologies.
5. Mariabackup is a fork of XtraBackup lineage-wise, but behavior, version coupling, and edge cases differ enough that “use whichever” is risky.
6. System tables and data dictionary evolved differently: MySQL 8 introduced major dictionary changes; MariaDB took a different route. Tooling that scrapes mysql.* tables can break.
7. JSON is a recurring pain point: MariaDB historically implemented JSON as a string with functions; MySQL treats it as a native type with different indexing semantics.
8. Authentication plugins diverged: MySQL/Percona moved through caching_sha2_password; MariaDB leaned on different plugin sets and defaults depending on version.
9. Optimizer paths are not interchangeable: both have cost models and heuristics that change query plans in ways that are “legal” but operationally explosive.

These differences don’t mean one is “bad.” They mean the same playbook won’t always work. Your job is to know which assumptions you’re making, then kill the ones that aren’t true.

One quote that should be stapled to every migration plan: “Hope is not a strategy.” — James Cameron.

Compatibility map: where MariaDB and Percona Server diverge

1) Versioning and feature targeting

Percona Server generally tracks upstream MySQL releases (and their semantics), so its compatibility target is “MySQL behavior + extras.” MariaDB targets “MariaDB behavior,” while remaining MySQL-ish for common use cases.

If your application vendor says “MySQL 8 compatible,” that usually maps more naturally to Percona Server for MySQL 8 than to MariaDB. If your vendor says “MariaDB supported,” don’t interpret it as “MySQL supported.” Those are two different promises.

2) System tables, metadata, and tooling assumptions

Many corporate scripts do crimes against the mysql database. They query legacy system tables directly. Or they parse SHOW PROCESSLIST output like it’s a stable API. Or they assume information_schema columns exist the same way everywhere.

That stuff works—until it doesn’t. In migrations, it’s often the tooling that fails first, not the database.

3) Plugins and features that sound similar but are not

Authentication plugins, audit plugins, password validation, encryption—names overlap, behavior doesn’t. “We use the audit plugin” is not a requirement; it’s a specification hole unless you can name which one, and which events, and where logs go.

4) InnoDB: “same engine name,” different patches

Both worlds use InnoDB, but with different patch sets, defaults, and sometimes different instrumentation. Percona is famous for extra metrics and performance-related changes. MariaDB historically shipped XtraDB in some versions, then converged toward InnoDB again. Operationally, this shows up as different defaults, different tuning sweet spots, and different “it’s fine” thresholds.

The practical takeaway: don’t assume your InnoDB tuning file is portable. You can keep the spirit, not the literal values.

Replication and HA: GTID, failover, and the sharp edges

GTID: the big compatibility fork in the road

If you take one thing from this article, take this: MariaDB GTID and MySQL/Percona GTID are different systems. They solve similar problems with different formats and different operational behaviors.

That matters for:

• Failover automation: tools that assume MySQL GTID semantics may do unsafe promotion on MariaDB, and vice versa.
• Mixed clusters: “We’ll run MariaDB replicas off Percona primary for a while” is not a casual decision. It’s usually a short-lived bridge with strict constraints, not a steady-state architecture.
• Point-in-time recovery: your binlog-based recovery workflow may need adjustments, especially around GTID strictness and consistency.

Replication filters and row-based behavior

Statement-based replication is the land where ghosts live. If you’re migrating, force yourself into row-based replication unless you have a strong reason not to. Differences in function determinism, collation behavior, or SQL mode can make statement replication “technically successful” while corrupting data slowly.

Group replication and Galera expectations

Percona Server is often deployed with MySQL-style replication topologies or Percona XtraDB Cluster (Galera-based). MariaDB also has Galera variants. The similarity ends when you realize each ecosystem has its own defaults, operational tooling, and edge-case handling.

If your HA story depends on “Galera will handle it,” you’re outsourcing correctness to a system that still needs you to define conflict behavior, write patterns, and quorum decisions.

Backup and restore: XtraBackup vs mariabackup and the restore reality

Backups are where compatibility claims go to die quietly. The database starts, queries work, everyone relaxes—until a restore test reveals that your backup tooling was “mostly compatible” with the server you actually run.

XtraBackup (Percona) vs mariabackup (MariaDB)

Operationally, both aim to do hot physical backups of InnoDB. In practice:

• Version coupling: backup tools are picky about server versions. “Close enough” becomes “won’t prepare backup.”
• Encryption/compression differences: options and defaults vary; restore pipelines break if you assume flags are portable.
• Incrementals: work, until they don’t—especially across upgrades or changed redo log settings.

My hard rule: restore tests are part of the migration. Not after. Not “we’ll do it later.” If you can’t restore, you don’t have a database, you have a rumor.

Joke #2: Backups are like parachutes: if you only test them once, it’s usually the last time you’ll need them.

Security and auth: plugins, TLS, and client surprises

Authentication plugins can make “compatible” clients fail

Client libraries often bake in assumptions about default auth plugins. When MySQL shifted defaults (notably around caching_sha2_password in MySQL 8), it triggered a multi-year parade of connection issues across languages and OS packages.

MariaDB made different choices and offered different plugins. Percona tracks MySQL behavior closely. That means the same application container image might connect fine to one and fail to the other—without any code changes.

TLS and cipher policy mismatches

TLS “works” until your compliance team enforces new cipher suites or minimum versions. Different server builds and distro packages can have different OpenSSL linkage, different defaults, and different accepted cipher sets.

Make security explicit: define TLS version, cipher expectations, and client library versions as part of your runbook.

Optimizer and performance: the “same query, different plan” problem

The most expensive outages are the ones where nothing is broken. It’s just slower. Slow enough to cascade.

Why plans drift

Even when SQL syntax is supported, the optimizer can pick different join orders, indexes, and temporary table strategies. Reasons include:

• Different cost models and statistics handling
• Different defaults for temporary tables, memory limits, and sort buffers
• Different interpretations of hints or different available hint syntax
• Different collation behavior affecting index usage

Practical guidance

Before migrating, capture representative query plans and actual runtime behavior. Not just EXPLAIN—also latency distribution, rows examined, and contention. After migrating, compare again under the same dataset shape.

If you’re not going to do this, be honest: you’re gambling, not engineering.

Observability and tooling: what your dashboards won’t tell you

Most “MySQL monitoring” setups are a pile of assumptions: which status variables exist, which performance schema tables are enabled, how slow logs look, and which user has permissions to read everything.

Percona ecosystems often lean on Percona Toolkit conventions and extended metrics. MariaDB environments may have different instrumentation defaults and different performance schema maturity depending on version. Both can be made observable, but not by assuming your exporter config is portable.

Also: check your admin scripts. Anything that scrapes SHOW ENGINE INNODB STATUS and greps for English strings is a liability. It will work until it doesn’t, and then it will page you at 03:12 with nonsense.

Fast diagnosis playbook

This is the “we just migrated and now it’s slow/unstable” drill. The goal is to find the bottleneck in minutes, not to win an argument about whose database is better.

First: identify whether the limit is CPU, IO, locks, or replication

• CPU: high user CPU, many runnable threads, query plans changed, missing indexes, or new sort/temp behavior.
• IO: high await times, buffer pool misses, redo/flush pressure, slow storage, wrong innodb_flush_method.
• Locks: spikes in lock waits, deadlocks, long transactions, different isolation defaults.
• Replication: replica lag, relay log apply bottlenecks, GTID mismatch, row format changes.

Second: check the top 3 queries and their plans

Don’t browse a thousand metrics. Identify the biggest offenders (by total time and p95). Compare plans against baseline.

Third: validate the operational basics

• Are binary logs configured as expected?
• Is the server in the right SQL mode?
• Did authentication changes force clients into reconnect storms?
• Did the backup/restore path change the data layout (e.g., different file-per-table settings)?

Fourth: decide whether to rollback, tune, or patch queries

Rollback is not failure; it’s control. If your restore and re-cutover are rehearsed, rollback is a routine operation. If they aren’t, you’re stuck “tuning live” while bleeding.

Common mistakes: symptoms → root cause → fix

1) App can’t connect after migration

Symptoms: “Authentication plugin not supported”, handshake failures, or TLS errors from clients.

Root cause: auth plugin defaults differ; client library too old; TLS policy mismatch.

Fix: align auth plugin to what clients support; upgrade client libs; explicitly configure TLS and verify with a known-good client.

2) Queries are correct but slower by 5–50×

Symptoms: p95 latency spikes, CPU up, slow log full of queries that used to be fine.

Root cause: optimizer plan drift; stats differences; different temp table behavior; collation/index use changed.

Fix: capture and compare EXPLAIN/EXPLAIN ANALYZE (where available), update stats, add or adjust indexes, consider query hints only as a last resort.

3) Replication “works” but failover breaks

Symptoms: failover tool refuses to promote, or promotes but replicas won’t reattach cleanly.

Root cause: GTID semantic mismatch; mixed-mode topology assumptions; different binlog settings.

Fix: choose one GTID universe; standardize replication settings; test promotion and rejoin under load in staging.

4) Backups succeed, restores fail

Symptoms: backup job green; restore test fails at prepare phase or server won’t start.

Root cause: tool/server version mismatch; wrong flags; encryption/compression mismatch; missing redo logs expectations.

Fix: pin backup tool versions to server versions; run periodic restore drills; validate prepared backup boots cleanly.

5) Sudden lock contention after migration

Symptoms: rising lock waits, deadlocks, throughput drops despite similar query mix.

Root cause: different defaults (isolation, autocommit patterns exposed), changed execution plans causing more rows scanned/locked, long transactions from batch jobs.

Fix: identify blocking transactions, shorten transaction scopes, add indexes to reduce scanned rows, review isolation level and workload patterns.

6) Monitoring breaks or shows nonsense

Symptoms: dashboards missing metrics, exporters erroring, alert spam about “unknown variable.”

Root cause: metric names and availability differ; performance schema config differs; privilege differences.

Fix: update exporters and queries; enable required instrumentation intentionally; stop scraping unstable internals.

Three corporate mini-stories from the trenches

Mini-story 1: the incident caused by a wrong assumption

A mid-sized SaaS company decided to “standardize” databases. One product ran MariaDB, another ran Percona Server. The plan sounded simple: move everything to one engine so the on-call team could stop context-switching.

The migration team focused on schema and data movement. They validated that the app started, that CRUD worked, and that smoke tests passed. They assumed replication failover would behave the same because “it’s all MySQL.”

Two weeks later, a primary node died. The failover automation promoted a replica, and the app came back. Then the old primary returned, and rejoining it failed in a way the automation didn’t handle. The cluster split into “I think I’m ahead” camps, and the team discovered that their GTID assumptions weren’t portable across the engines they’d mixed during the transition.

The fix was not heroic tuning. It was architectural honesty: they froze mixed topologies, rebuilt replicas from clean backups, and only allowed one GTID model in any replication domain. The real lesson wasn’t about GTID syntax. It was about not treating HA semantics as an implementation detail.

Mini-story 2: the optimization that backfired

A large enterprise migrated from one MySQL variant to another to get better performance instrumentation and lower latency. After cutover, they noticed higher IO and worse tail latencies. So they did what many teams do: they turned knobs.

Someone increased buffer sizes and raised concurrency-related settings because “more threads equals more throughput.” They also tweaked flushing behavior to reduce fsync frequency. On paper, it looked like classic tuning.

For about a day, throughput improved. Then they hit a traffic spike. The server started stalling in bursts: short periods of normal behavior, followed by ugly pauses where everything queued up. The root cause was a flush/redo pressure pattern: they had traded consistent latency for periodic cliff-falls. The tuning amplified the engine’s worst moment instead of smoothing it.

They rolled back the changes, profiled again, and discovered the real regression: a handful of queries had flipped to plans that used large temporary tables. Fixing indexes and query patterns reduced IO more than any buffer change. The “optimization” had been a distraction, and it nearly became the permanent config because it briefly looked good.

Mini-story 3: the boring but correct practice that saved the day

A finance-adjacent company had a rule that annoyed everyone: quarterly restore drills, not optional. Every drill included restoring a full backup, applying binlogs to a target timestamp, and running a simple consistency check suite.

When they migrated from MariaDB to Percona Server, the drill surfaced a subtle issue early. Their backup job was green, but the prepared backup intermittently failed to start after restore because of a version mismatch between the backup tool container and the server version in production.

Because the drill happened before cutover, the fix was mundane: pin versions, bake a tested backup image, and add a compatibility check to CI that ran a tiny backup/prepare/restore cycle on every version bump.

Months later, they had an actual incident: accidental data deletion. The team restored cleanly, applied binlogs to the minute, and returned service without improvising. Nobody celebrated, because it was boring. That’s the highest compliment in ops.

Practical tasks (commands + outputs + decisions)

These are real tasks you can run on Linux hosts and within the database. Each includes what the output means and what you decide next. Run them before and after a migration, and when diagnosing production weirdness.

Task 1: Confirm server identity and version lineage

cr0x@server:~$ mysql -NBe "SELECT VERSION(), @@version_comment, @@version_compile_machine;"
10.11.6-MariaDB MariaDB Server x86_64

What it means: This tells you which family you’re actually running. @@version_comment often includes “Percona Server” or “MariaDB Server”.

Decision: Map your compatibility target. If you expected MySQL/Percona semantics and you see MariaDB, stop and re-check GTID, JSON, and plugin assumptions.

Task 2: Check SQL mode drift (silent behavior changer)

cr0x@server:~$ mysql -NBe "SELECT @@sql_mode;"
STRICT_TRANS_TABLES,ERROR_FOR_DIVISION_BY_ZERO,NO_ENGINE_SUBSTITUTION

What it means: SQL mode affects data validation, implicit conversions, and error handling.

Decision: Align SQL mode across old and new servers before comparing behavior. If you change it during migration, you’re changing app semantics.

Task 3: Verify default authentication plugin

cr0x@server:~$ mysql -NBe "SHOW VARIABLES LIKE 'default_authentication_plugin';"
default_authentication_plugin	mysql_native_password

What it means: Different defaults can break old clients.

Decision: If clients are legacy, keep a compatible plugin or upgrade clients first. Don’t “fix” production by weakening auth without tracking it.

Task 4: Inspect user plugins actually in use

cr0x@server:~$ mysql -NBe "SELECT user, host, plugin FROM mysql.user ORDER BY plugin, user LIMIT 10;"
app	%	mysql_native_password
repl	10.%	mysql_native_password

What it means: Even if the default is safe, specific users may be using incompatible plugins.

Decision: If you see plugins not supported on the target engine, you need a credential migration plan (and likely a client library audit).

Task 5: Check InnoDB and redo/flush basics

cr0x@server:~$ mysql -NBe "SHOW VARIABLES WHERE Variable_name IN ('innodb_flush_method','innodb_flush_log_at_trx_commit','innodb_buffer_pool_size');"
innodb_buffer_pool_size	17179869184
innodb_flush_log_at_trx_commit	1
innodb_flush_method	O_DIRECT

What it means: These settings heavily influence latency, durability, and IO behavior.

Decision: Do not copy configs blindly. Re-evaluate per engine and per storage. If you change durability (innodb_flush_log_at_trx_commit), document the risk and get explicit sign-off.

Task 6: Validate binlog format and row image

cr0x@server:~$ mysql -NBe "SHOW VARIABLES WHERE Variable_name IN ('log_bin','binlog_format','binlog_row_image');"
log_bin	ON
binlog_format	ROW
binlog_row_image	FULL

What it means: These influence replication safety and compatibility.

Decision: For migrations, ROW + FULL is the conservative default. If you change to MINIMAL for performance, test downstream consumers and replication carefully.

Task 7: Check GTID mode indicators

cr0x@server:~$ mysql -NBe "SHOW VARIABLES LIKE '%gtid%';" | head
gtid_domain_id	0
gtid_strict_mode	ON
gtid_binlog_pos	0-1-12345

What it means: These variables are MariaDB-flavored GTID indicators (domain/server/sequence style).

Decision: If you’re moving to/from MySQL/Percona GTID, plan for GTID translation or a topology reset. Don’t wing it during a failover event.

Task 8: Spot replication lag and the reason (IO vs SQL thread)

cr0x@server:~$ mysql -e "SHOW SLAVE STATUS\G" | egrep "Slave_IO_Running|Slave_SQL_Running|Seconds_Behind_Master|Last_SQL_Error|Retrieved_Gtid_Set|Executed_Gtid_Set" -n
3:Slave_IO_Running: Yes
4:Slave_SQL_Running: Yes
32:Seconds_Behind_Master: 18
48:Last_SQL_Error:
78:Retrieved_Gtid_Set:
79:Executed_Gtid_Set:

What it means: If IO and SQL threads run but lag increases, apply is slow or workload spikes. Error fields help detect incompatibilities.

Decision: If lag is persistent post-migration, inspect disk IO and query patterns on replicas; consider parallel replication settings appropriate to your engine/version.

Task 9: Capture top waits quickly (InnoDB mutex/lock pressure proxy)

cr0x@server:~$ mysql -NBe "SHOW GLOBAL STATUS LIKE 'Innodb_row_lock%';"
Innodb_row_lock_current_waits	3
Innodb_row_lock_time	89123
Innodb_row_lock_time_avg	1123
Innodb_row_lock_time_max	9000
Innodb_row_lock_waits	79

What it means: Rising waits/time indicate contention, often from plan changes or long transactions.

Decision: If this jumped after migration, find the blocking transactions and compare execution plans for the hot tables.

Task 10: Identify the longest running transactions

cr0x@server:~$ mysql -e "SELECT trx_id, trx_started, trx_mysql_thread_id, trx_rows_locked, trx_rows_modified FROM information_schema.innodb_trx ORDER BY trx_started LIMIT 5;"
+--------+---------------------+--------------------+----------------+------------------+
| trx_id | trx_started         | trx_mysql_thread_id| trx_rows_locked| trx_rows_modified|
+--------+---------------------+--------------------+----------------+------------------+
| 123ABC | 2025-12-30 01:12:09 | 9821               | 44012          | 12               |
+--------+---------------------+--------------------+----------------+------------------+

What it means: Long transactions hold locks and inflate undo/redo work.

Decision: If you see long-lived transactions post-migration, hunt the application code path or batch job. Sometimes a changed plan makes a transaction take 10× longer and everything else looks “mysteriously locked.”

Task 11: Compare query plans for a known hot query

cr0x@server:~$ mysql -e "EXPLAIN SELECT * FROM orders WHERE customer_id=123 AND status='OPEN' ORDER BY created_at DESC LIMIT 50;"
+----+-------------+--------+------+------------------------+--------------------+---------+-------+------+-----------------------------+
| id | select_type | table  | type | possible_keys          | key                | key_len | ref   | rows | Extra                       |
+----+-------------+--------+------+------------------------+--------------------+---------+-------+------+-----------------------------+
|  1 | SIMPLE      | orders | ref  | idx_customer_status_dt | idx_customer_status_dt | 8   | const | 120  | Using where; Using filesort |
+----+-------------+--------+------+------------------------+--------------------+---------+-------+------+-----------------------------+

What it means: “Using filesort” might be fine—or it might be your new bottleneck if it wasn’t there before.

Decision: If plan changed, consider a covering index that supports the ORDER BY. Validate with real latency and rows examined, not just EXPLAIN aesthetics.

Task 12: Check temporary table behavior and spills

cr0x@server:~$ mysql -NBe "SHOW GLOBAL STATUS LIKE 'Created_tmp%';"
Created_tmp_disk_tables	12409
Created_tmp_tables	70211
Created_tmp_files	88

What it means: Disk temp tables and tmp files often correlate with sudden slowdowns after optimizer changes.

Decision: If disk temp tables spike after migration, focus on query plans and indexes first. Only then consider temp table sizing changes.

Task 13: Confirm character set and collation defaults

cr0x@server:~$ mysql -NBe "SHOW VARIABLES WHERE Variable_name IN ('character_set_server','collation_server');"
character_set_server	utf8mb4
collation_server	utf8mb4_general_ci

What it means: Collation changes can break uniqueness assumptions and index usage.

Decision: If defaults differ from your baseline, set them explicitly and verify app expectations (especially around sorting and case sensitivity).

Task 14: Validate storage and filesystem IO latency (host-side reality)

cr0x@server:~$ iostat -x 1 3
Linux 6.5.0 (server) 	12/30/2025 	_x86_64_	(8 CPU)

avg-cpu:  %user   %nice %system %iowait  %steal   %idle
          32.10    0.00    6.20    7.80    0.00   53.90

Device            r/s     w/s   r_await   w_await   aqu-sz  %util
nvme0n1         220.0   480.0     2.10     8.70     4.20   92.0

What it means: High w_await and %util point to write pressure. Migrations often change write patterns (different redo/log behavior, different temp table usage).

Decision: If storage is saturated, stop “database tuning” and fix IO capacity or reduce write amplification (query/index fixes, batching, flush settings only with durability awareness).

Task 15: Quick check for filesystem mount options that sabotage databases

cr0x@server:~$ findmnt -no TARGET,FSTYPE,OPTIONS /var/lib/mysql
/var/lib/mysql ext4 rw,relatime

What it means: Some mount options can impact latency. relatime is generally fine; other options (or exotic setups) may not be.

Decision: If you see surprising options (or network filesystems), treat that as a primary suspect for performance and durability issues.

Task 16: Validate backup tool version and server version alignment

cr0x@server:~$ xtrabackup --version
xtrabackup version 8.0.35 based on MySQL server 8.0.35 Linux (x86_64)

What it means: Backup tools advertise their compatibility target. Mismatch is a restore failure waiting to happen.

Decision: Pin the tool version to what you run. If you’re on MariaDB, prefer mariabackup aligned to that MariaDB major line.

Checklists / step-by-step plan

Plan A: You want Percona Server because you need MySQL-true compatibility

1. Inventory app expectations: vendor support matrix, SQL features used (JSON, window functions, generated columns), and client library versions.
2. Standardize SQL mode and character set: set explicit values; don’t inherit defaults.
3. Replication model decision: pick GTID semantics and stick to them. Don’t mix MariaDB GTID with MySQL GTID in steady state.
4. Tooling audit: monitoring exporters, backup scripts, failover automation, schema migration tooling—test them on the target engine.
5. Performance baseline: capture top queries, p95/p99 latency, rows examined, temp table rates, buffer pool hit rates.
6. Dry-run restore: create a full restore from backups into an isolated environment and run consistency checks.
7. Staged cutover: dual-write if you can justify it; otherwise use replica promotion and a rehearsed rollback.

Plan B: You want MariaDB because you’re committing to its ecosystem

1. Stop calling it “MySQL” internally: label it MariaDB in runbooks and dashboards. That reduces wrong assumptions.
2. Confirm feature usage: if you rely on MySQL 8-specific semantics, be careful. Test the exact MariaDB version you’ll run.
3. Adopt MariaDB-native tooling: especially for backup/restore and GTID-based automation.
4. Validate JSON usage: check column types and indexing expectations; avoid assuming native JSON behavior if you’re coming from MySQL.
5. Re-tune for your storage: especially temp table behavior and flushing patterns; don’t port configs as if they were container env vars.
6. Failover rehearsal: simulate node loss, promotion, and rejoin. Do it twice: once quiet, once during load.

Minimal “no surprises” migration acceptance criteria

• You can restore to a new host and boot the server cleanly.
• Failover works and replicas reattach without manual surgery.
• Top 20 queries have stable plans and acceptable tail latency.
• Monitoring and alerting work without “unknown variable” noise.
• Client auth and TLS work across every production client variant.

FAQ

1) Is Percona Server a drop-in replacement for MySQL?

Usually, yes—within the same major MySQL line—because it tracks upstream MySQL closely. Still validate plugins, defaults, and backup tooling.

2) Is MariaDB a drop-in replacement for MySQL?

Sometimes for basic apps, but it’s riskier as MySQL versions advance. If you need “MySQL 8 behavior,” treat MariaDB as a different database and test accordingly.

3) Is MariaDB a drop-in replacement for Percona Server?

Not reliably. The protocol may work, but GTID, system tables, plugins, and optimizer behavior can diverge enough to break automation and performance expectations.

4) Can I replicate from Percona Server to MariaDB (or the other way)?

You can sometimes do it as a temporary bridge with strict constraints (binlog format, supported SQL, careful GTID planning). Don’t assume it’s safe long-term without explicit validation.

5) What’s the biggest hidden trap in MariaDB ↔ Percona migrations?

GTID and failover semantics. It’s not the SQL. It’s what happens at 2 a.m. when a node dies and your automation makes assumptions.

6) Should I copy my my.cnf tuning from one to the other?

No. Start from a conservative baseline and port only settings you understand. Then tune with measurements. Blind copy is how you get periodic stalls and “it was fine before.”

7) Which one is faster?

Wrong question. The fastest database is the one where your hot queries use good plans and your IO isn’t saturated. Either engine can win or lose depending on workload and tuning.

8) Do I need different backup tooling?

Yes, plan for it. Use tooling aligned to your server family and version. And run restore drills—because compatibility claims don’t restore data.

9) How do I choose if my vendor only supports “MySQL”?

Ask what they mean by MySQL: version, auth plugin expectations, GTID usage, backup expectations. If they test against Oracle MySQL 8, Percona Server for MySQL 8 is usually the safer match.

10) Can I avoid these issues by using containers and Kubernetes?

No. Containers are excellent at packaging surprises consistently. You still need behavioral compatibility, tested backups, and rehearsed failover.

Next steps you can actually do this week

1. Run the practical tasks on your current fleet and write down the results: version, SQL mode, auth plugins, binlog format, GTID variables.
2. Pick a single compatibility target: “MySQL 8 semantics” (lean Percona) or “MariaDB semantics” (commit to MariaDB). Stop hoping you can get both for free.
3. Do one restore drill into an isolated host and prove the server boots and the app can run a small workload.
4. Rehearse failover in staging with the same automation you’ll use in production. If you don’t have automation, your first failover is a live experiment.
5. Baseline and compare plans for your top queries. If you find regressions, fix queries and indexes before you touch “tuning knobs.”

If you want a clean rule: Percona Server is generally the safer “MySQL-compatible” choice; MariaDB is a solid database when you treat it as MariaDB and stop pretending it’s MySQL with a different logo.