Database Support · 10 Engines, One Agreement
Database Support Services — Multi-Engine, Named Engineers
Database support services provide enterprise production incident response, proactive maintenance, and reliability engineering across multi-engine database tiers. JusDB supports 10 engines—including MySQL, PostgreSQL, MongoDB, Redis, and Cassandra—under one agreement with agreed initial-response targets, named senior DREs, and no L1 callback queue.
Initial-response targets are 2 to 4 hours during covered business hours, Mon–Fri 09:00–18:00 IST (UTC+5:30). Where your service agreement includes 24x7 on-call, the initial-response target for P1 incidents is 30 minutes. Targets are not resolution guarantees.
Production database support across MySQL, PostgreSQL, MongoDB, Cassandra, MariaDB, SQL Server, Aerospike, TiDB, Redis, and Valkey — one agreement, one on-call rotation, one set of response targets. Senior database engineers answer your Sev-1 within your agreement's initial-response target. No L1 callback queue, no escalation gates.
Vendor support failing you — sound familiar?
- Sev-1 ticket open 6 hours — Oracle MySQL Enterprise paid support has the engineer asking for a config file and going silent. Production is still down, you don't know if anyone's actually working it.
- L1 cycling through checklists — "have you restarted", "send us the logs", "is the disk full" — 90 minutes burned before anyone competent looks at the problem.
- Cross-engine incidents — your platform is MySQL + Redis + Kafka CDC, and you have three separate vendor contracts that all point at each other when something breaks.
JusDB database support: agreed initial-response targets, named senior engineers, no L1 queue, 10 engines under one agreement. Book a support scoping call →
10 database engines, one support contract
Click any engine for engine-specific support detail. We cover both managed-service (Atlas, RDS, Aurora, ElastiCache) and self-managed clusters under the same agreement.
MySQL
Percona Server, MariaDB, Aurora MySQL, RDS, GCP CloudSQL
Support detailPostgreSQL
Patroni, RDS, Aurora PG, GCP CloudSQL, Azure
Support detailMongoDB
Atlas, DocumentDB, self-hosted, mongos sharded clusters
Support detailCassandra
DataStax Enterprise, ScyllaDB, Astra
Support detailMariaDB
Galera Cluster, MaxScale, MariaDB SkySQL
Support detailSQL Server
Always-On AG, Azure SQL MI, RDS for SQL Server, Linux SQL
Support detailAerospike
Community + Enterprise, XDR, hybrid memory
Support detailTiDB
PingCAP managed, self-hosted, TiKV + TiFlash topology
Support detailRedis
OSS, Stack, Enterprise, ElastiCache, MemoryDB
Support detailValkey
Self-managed, ElastiCache Valkey engine
Support detailInitial-response targets by service level
Severity is classified at incident open, not at vendor convenience. Targets are set in your service agreement.
Business hours
For incidents and requests raised during covered business hours.
- Initial-response target: 2 to 4 hours · During covered business hours
- Human coverage: Mon–Fri 09:00–18:00 IST (UTC+5:30)
24x7 on-call
For P1 incidents at any hour, where your service agreement includes 24x7 on-call.
- Initial-response target: 30 minutes · P1 incidents
- Human coverage: 24x7 on-call
Initial-response targets, not resolution guarantees. The target for your engagement is set in your service agreement. 24x7 on-call is available under your service agreement.
Three ways to engage
Pick the shape that fits your platform's incident profile and team structure.
Retainer
Monthly engineering hours with initial-response targets set in your service agreement. 24x7 on-call is available under the agreement.
Per-Instance Management
Billed per standalone instance, HA cluster, or region, with coverage and response targets set in the service schedule.
Larger estates
Severity-based response targets defined in the agreement.
Every engagement covers
Sev-1 Database Failure Modes We Intervene Against
When production databases go down, generic cloud support checklists waste critical minutes. Our named senior DREs intervene against these catastrophic production failure modes:
Cascading Connection Lock Spikes & Thread Pool Exhaustion
A sudden surge in unindexed queries or long-running transactions locks row locks and exhausts the maximum database connection pool. New client requests queue up, cascading back to API web servers and taking the entire application offline.
Our on-call DREs isolate blocking PIDs using non-blocking pg_terminate_backend / KILL QUERY scripts, deploy emergency transaction-mode pooling, and throttle rogue queries.
Cross-Engine Polyglot Outages with Vendor Finger-Pointing
A distributed transaction stall between PostgreSQL, Redis cache invalidations, and Kafka CDC pipelines causes data desynchronization. Multiple single-engine vendor support contracts blame each other, prolonging downtime by hours.
JusDB provides a single, unified on-call rotation covering all 10 engines simultaneously, diagnosing distributed pipeline latency end-to-end without vendor finger-pointing.
Silent Replication Stream Desync & Stale Read Disasters
Replication lag silently grows on read replicas under heavy write spikes. Applications reading from laggy read replicas serve stale or inconsistent user data, triggering billing discrepancies or duplicate order creations.
We establish real-time heartbeat lag tracking with automated read-traffic shedding, temporarily redirecting critical queries to the primary until replication parity is re-established.
Our on-call DREs execute non-blocking diagnostics to identify blocking transactions and connection spikes without compounding query wait queues:
-- Identify root blocking query PID and waiting transactions
SELECT blocked_locks.pid AS blocked_pid,
blocked_activity.usename AS blocked_user,
blocking_locks.pid AS blocking_pid,
blocking_activity.usename AS blocking_user,
blocked_activity.query AS blocked_statement,
blocking_activity.query AS blocking_statement
FROM pg_catalog.pg_locks blocked_locks
JOIN pg_catalog.pg_stat_activity blocked_activity
ON blocked_activity.pid = blocked_locks.pid
JOIN pg_catalog.pg_locks blocking_locks
ON blocking_locks.locktype = blocked_locks.locktype
AND blocking_locks.database IS NOT DISTINCT FROM blocked_locks.database
AND blocking_locks.relation IS NOT DISTINCT FROM blocked_locks.relation
AND blocking_locks.pid != blocked_locks.pid
JOIN pg_catalog.pg_stat_activity blocking_activity
ON blocking_activity.pid = blocking_locks.pid
WHERE NOT blocked_locks.granted;-- 1. Inspect non-sleeping threads running > 5 seconds
SELECT id, user, host, db, command, time, state,
LEFT(info, 100) AS query_snippet
FROM information_schema.processlist
WHERE command != 'Sleep' AND time > 5
ORDER BY time DESC LIMIT 10;
-- 2. Inspect InnoDB lock wait relationships
SELECT r.trx_id waiting_trx, r.trx_mysql_thread_id waiting_thread,
b.trx_id blocking_trx, b.trx_mysql_thread_id blocking_thread
FROM performance_schema.data_lock_waits w
JOIN performance_schema.data_locks r ON r.engine_lock_id = w.requesting_engine_lock_id
JOIN performance_schema.data_locks b ON b.engine_lock_id = w.blocking_engine_lock_id;How JusDB Support compares to alternative models.
Vendor callback queues and generic helpdesk triage waste precious time during production downtime. Here is how JusDB compares to vendor enterprise support, generic MSPs, and internal on-call rotations.
| Support Dimension | JusDB Database Support | Vendor Enterprise Support | Generic MSP Helpdesk | Internal On-Call Devs |
|---|---|---|---|---|
| Sev-1 Response Targets & Escalation | Named senior DBREs join your incident bridge. Initial-response targets: 2 to 4 hours in covered business hours; 30 minutes for P1 incidents with 24x7 on-call. Targets, not resolution guarantees. | 1 to 2 hour initial acknowledgement targets; often handled by automated ticket routing bots | 1 to 4 hour response windows with ticket queues handled by generic offshore network helpdesks | Unreliable on-call paging; engineers wake up to alert fatigue or miss pages during overnight rotations |
| Engineer Caliber & No L1 Queue | Zero L1 gatekeeping. Your first interaction is directly with a senior database reliability engineer who has access to your runbook | Multi-tier escalation; 60–90 minutes wasted cycling through junior L1 triage checklists before reaching an engineer | Generalist sysadmins following standard operating procedures without deep database internals knowledge | Application developers who lack deep database engine forensics, leading to trial-and-error troubleshooting during outages |
| Multi-Engine Platform Scope | One unified contract covering 10+ engines (PostgreSQL, MySQL, MongoDB, Redis, Cassandra, SQL Server) under a single service agreement | Single-engine silo. If your outage involves MySQL + Redis + Kafka, each vendor points fingers at the other | Basic administration across multiple engines without specialized high-availability or query optimization tuning | Tribal knowledge split across different team members who each only know one database technology |
| Managed & Hybrid Cloud Coverage | Seamless coverage across AWS (RDS/Aurora), GCP (Cloud SQL), Azure, MongoDB Atlas, Kubernetes, and bare-metal | Strictly limited to the vendor's proprietary cloud service; on-prem or multi-cloud topologies are unsupported | Rigid hosting templates with little flexibility for modern cloud-native or Kubernetes database operators | Struggles to balance differing operational semantics across cloud-managed and self-hosted databases |
| Proactive Health & Capacity Forecasting | Weekly telemetry reviews, proactive index bloat / replication lag monitoring, and quarterly capacity forecasting | Purely reactive break-fix; vendor support never logs into your cluster unless you open an explicit ticket | Generic automated server uptime pings without database query performance or replication lag analysis | Teams are too busy shipping product features to conduct regular database maintenance and capacity audits |
| Blameless Postmortems & Runbooks | Engineers facilitate comprehensive postmortems, identify root causes, and author custom runbooks to prevent recurrence | Brief generic root-cause statements that attribute failures to user configuration or cloud platform hiccups | Tickets closed with 'service restarted' status without conducting in-depth root cause analysis | Postmortems are skipped due to sprint deadlines, leaving identical failure modes to repeat months later |
Common questions
Stop the callback queue.
Get database support with agreed response targets across 10 engines, with named senior engineers.