Database Support

24/7 Database Support with a 15-Minute Emergency SLA

Database support services for the open source databases enterprises run in production: PostgreSQL, MySQL, MongoDB, Redis and Valkey, Apache Cassandra, ClickHouse, Elasticsearch and OpenSearch, Apache Druid, Greenplum, GemFire and Memcached. Self-managed, on Kubernetes, or on managed cloud services such as Amazon RDS, Aurora and MongoDB Atlas. One support contract and one SLA, a 15-minute response for P1 incidents, and every ticket reaches a named senior engineer who specializes in that database.

Senior Database engineers on call right now — 24/7/365
15 min emergency SLA24 /7 global coverage130 + enterprise customers26 + countries served

Trusted for Mission-Critical Database by Teams in Finance, Healthcare, Defense, Telecom, and More

Incident Triage

Database problems we fix every week

These are real symptoms from real Database production environments — and the first thing our engineers check when one comes in.

PostgreSQL: WAL directory filling the disk with no increase in write traffic
What we check firstpg_replication_slots for an inactive slot. A slot left behind by a decommissioned replica or a paused CDC consumer retains WAL indefinitely, and PostgreSQL will fill the volume defending a subscriber that is never coming back. We also check for a silently failing archive_command.
Typical resolutionUnder 1 hour
MySQL: replica lag climbing into hours during the nightly batch
What we check firstWhether apply is actually parallel: replica_parallel_workers and replica_parallel_type, plus binlog_transaction_dependency_tracking. A single large multi-row transaction serializes the whole apply pipeline regardless of worker count, so we look at transaction size before we look at hardware.
Typical resolution1–2 hours
MongoDB: replica set keeps electing a new primary several times a day
What we check firstHeartbeat latency between members, election metrics, and secondary apply lag. Network flap between availability zones and a secondary too slow to keep up are the two usual causes; priority and votes misconfiguration turns both into a loop.
Typical resolution1–3 hours
Redis or Valkey: commands intermittently timing out under normal load
What we check firstSLOWLOG for O(N) commands on the single-threaded command loop. One KEYS, one unbounded SMEMBERS on a large set, or a Lua script iterating a big collection blocks every other client for its full duration.
Typical resolutionUnder 1 hour
Cassandra: read timeouts on a table with heavy deletes or short TTLs
What we check firstTombstone counts per read in the system log against tombstone_warn_threshold, and how long since compaction last purged them. Every delete and every expired TTL cell is a tombstone that must be scanned on each read until it ages past gc_grace_seconds and compacts away.
Typical resolution1–3 hours
ClickHouse: inserts failing with DB::Exception: Too many parts
What we check firstInsert batch size and frequency first. Every insert statement creates at least one part per partition, and background merges cannot keep up with thousands of tiny inserts per second. We also check partition key cardinality: partitioning by day is fine, partitioning by timestamp is not.
Typical resolutionUnder 1 hour
Elasticsearch or OpenSearch: cluster stuck yellow or red after a node restart
What we check firstThe allocation explain API for one unassigned shard. The answer is almost always a disk watermark (a node past flood_stage puts indices into read_only_allow_delete) or an allocation attribute rule that no remaining node satisfies.
Typical resolutionUnder 1 hour
Memcached: database CPU spikes to 100% seconds after a cache node drops
What we check firstWhether the client uses consistent hashing (ketama) or modulo hashing. Modulo remaps nearly every key on a ring change and sends the entire keyspace to the database at once. We check client configuration first, then add request coalescing on the hot keys.
Typical resolution1–2 hours

Resolution times reflect typical Database engagements under an active AceMQ support contract. Every P1 closes with a written root-cause analysis.

What's Included

Everything in your Database support contract

No add-on pricing for incidents. No per-ticket charges. One contract covers the whole surface.

Emergency Incident Response

Database down, disk full, replication broken, a cluster gone red, or a primary that will not accept writes. A senior engineer joins a live bridge within 15 minutes, 24/7, with access to diagnose rather than a ticket acknowledgement.

Root Cause Analysis

Every P1 closes with a written RCA: what failed, why, the fix applied, and the configuration, index, query or client change that stops it recurring. Delivered as standard, not on request.

Performance and Query Tuning

Slow queries, plan regressions, lock contention, memory and eviction pressure, and connection exhaustion, diagnosed against your real workload. Query optimization, index design, statistics, pooling and client settings, per database rather than one generic checklist of database performance tips.

Replication, High Availability and Failover

Replica sets, streaming and logical replication, Sentinel and cluster topologies, multi-datacenter Cassandra, and shard allocation. High availability setups such as Patroni and InnoDB Cluster reviewed, and failover tested with clients connected, so the first real failover is not the first test.

Upgrades and Migrations

Major version upgrades planned from the release notes and rehearsed with a rollback, plus migrations between self-managed PostgreSQL and Amazon RDS, Aurora, Azure Database or Cloud SQL, onto PostgreSQL from Oracle, SQL Server or MySQL, and from Redis to Valkey.

CVE Advisory and End-of-Life Versions

Alerts for CVEs that affect the exact version and extensions you run, with tested patch paths. Databases past community end of life stay supported, and for PostgreSQL 11 to 13, Redis and Valkey, AceMQ's OSSeva platform backports security fixes while the upgrade is planned.

Escalation Path

Your first hour of a Database outage

Most vendors publish an SLA number. This is what actually happens, minute by minute, when you page a senior AceMQ engineer.

T+0

You page us

Phone, email, or Slack — any channel reaches the on-call senior engineer directly. No web form, no tier-1 queue.

T+15

Named engineer live

A senior engineer who already knows your environment joins a live bridge. Zero cold-start, no re-explaining your topology.

T+30

Root cause isolated

Direct broker access, log and metric review, and a working hypothesis with a rollback plan before we touch anything.

Post

Written RCA

Documented root cause, the fix applied, and the prevention steps — delivered after every P1, not just when asked.

Response Times

SLA tiers, contractually guaranteed

Every tier reaches a senior Database engineer. There is no tier-1 triage layer to get through.

P1 — Emergency
15 min

Production down: primary unavailable, replication broken, disk full, cluster red, or writes refused

P2 — Critical
1 hour

Severe degradation, rising error rates, approaching capacity limits

P3 — High
4 hours

Performance issues, configuration problems, non-critical failures

P4 — Standard
Next day

Questions, guidance, best practices, non-urgent improvements

49+ Platforms Supported

We Support Your Entire Tech Stack

Database rarely fails in isolation. AceMQ covers the full surrounding infrastructure — so one team owns the whole path instead of pointing at each other.

Observability & Monitoring

PrometheusGrafanaDatadogNew RelicSplunk

Data Integration & Orchestration

Apache AirflowApache NiFiAirbytePentaho

API Management & Integration

KongApigeeMuleSoftWSO2
Databases covered

Open source databases we support, and where they run

Every database below is covered by the same 24/7 contract and the same 15-minute P1 SLA. Each has its own support page with the failure modes we see most and the versions covered.

DatabaseDeployments coveredTypical incidents
PostgreSQLSelf-managed PostgreSQL 12 to 17, Amazon RDS and Aurora PostgreSQL, Azure Database for PostgreSQL, Google Cloud SQL and AlloyDB, Kubernetes operatorsAutovacuum lag and bloat, WAL growth, wraparound warnings, connection exhaustion
Tanzu for PostgresPostgreSQL 13 to 17 under the Tanzu operator on Kubernetes and OpenShift, Patroni-managed HA clustersFreeze vacuum falling behind, connection storms on pod rolls, checkpoint stalls
MySQLMySQL 5.7 (end of life) through 8.4, Amazon RDS and Aurora MySQL, Azure, Cloud SQL, Percona Server, MariaDB, InnoDB ClusterReplica lag, gap-lock deadlocks, long ALTER statements, binlog growth
MongoDBMongoDB Atlas, Enterprise Advanced, Community 5.x to 8.x, Amazon DocumentDB, Percona Server for MongoDBElection storms, WiredTiger cache pressure, short oplog windows, shard key hot spots
RedisSelf-managed, Amazon ElastiCache and MemoryDB, Azure Cache and Azure Managed Redis, Memorystore, Redis Enterprise, Sentinel and ClusterLatency spikes, fork stalls, eviction storms, failovers that strand clients
ValkeyValkey 7.2 to 9.1, self-managed, Kubernetes, ElastiCache and Memorystore for Valkey, Tanzu for ValkeyI/O thread tuning, stuck slot migrations, OOM write rejections
Apache CassandraCassandra 3.11, 4.x and 5.0, DataStax Enterprise, Amazon Keyspaces, K8ssandra, multi-datacenterTombstones, oversized partitions, repairs past gc_grace_seconds
ClickHouseClickHouse Cloud, self-managed 23.x to 25.x, Keeper and ZooKeeper, Altinity builds and operatorToo many parts, memory limits, replication queues stalled behind Keeper
ElasticsearchElastic Cloud, ECK on Kubernetes, self-managed on AWS, Azure, Google Cloud and on premisesRed clusters, circuit breakers, oversharding, ILM rollover failures
OpenSearchAmazon OpenSearch Service and Serverless, self-managed OpenSearch 1.x to 3.xUnassigned shards, ISM failures, Elasticsearch client incompatibility
Apache DruidDruid 26 to 31 self-managed, Imply, Druid Operator on KubernetesKafka ingestion lag, segment handoff, broker timeouts
GreenplumGreenplum 5.x, 6.x and 7.x on vSphere, bare metal and cloudSegment failures, distribution skew, spill files filling disks
GemFire and Apache GeodeGemFire 9.x and 10.x, Apache Geode, Kubernetes and Tanzu PlatformGC pauses, members leaving the cluster, WAN sender backlog
MemcachedMemcached 1.5.x and 1.6.x, Amazon ElastiCache and Memorystore for MemcachedSlab calcification, eviction storms, connection limits, miss stampedes

Coverage as listed on each database's AceMQ support page. Links to every page are below.

Why AceMQ

What you get that you don't get elsewhere

One SLA Across Every Database

Most estates run three or four databases: a relational store, a cache, a search cluster, an analytics engine. One contract covers all of them with the same 15-minute P1 SLA, so an incident never stalls on which vendor or which contract it belongs to.

Specialists Per Database, Not Generalists

The engineer who answers a PostgreSQL wraparound warning is not the one who answers a Cassandra tombstone problem. What is shared is the SLA and the contract, not the expertise, and the same named engineers stay on your account.

No Tier-1 Triage Layer

You reach a senior database engineer directly by phone, email or Slack. Nobody collects details to pass along while the primary is down.

Managed Cloud and Self-Managed

RDS, Aurora, Atlas, ElastiCache and OpenSearch Service remove patching mechanics, not the problems that cause most incidents. Bloat, plan regressions, hot partitions and connection exhaustion are still yours, and we support all three deployment models.

Full Stack, Not Just the Database

We diagnose across the connection pooler, the ORM's query generation, storage latency, kernel settings and Kubernetes, because a surprising number of database incidents start one layer above or below the database.

Follow-the-Sun Coverage

Engineers across 26+ countries and every time zone, so a 3am replication break reaches someone who is already at work.

FAQ

Database support questions

Put a Senior Engineer Behind Every Database You Run

Whether you need emergency cover tonight, a major version upgrade planned, or one contract across PostgreSQL, MongoDB, Redis and Elasticsearch, AceMQ staffs it with named senior engineers. Support quotes returned within 24 hours.

Get in Touch

Talk to a Support Expert

Send us a message and we'll follow up within one business day — or book a free 30-min consultation directly.

305-204-2607
info@acemq.com
66 W. Flagler St. 9th Floor
Miami, FL 33130

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