MinervaDB Consultative Support · Full-stack database infrastructure engineering · 12 engines, 8 cloud DBaaS platforms
MinervaDB Consultative Support: Senior Engineers Across Every Database You Run
MinervaDB Consultative Support is the senior-practitioner partnership enterprises engage when the data tier has to run faster, scale further, stay available and pass every audit. We engineer PostgreSQL, MySQL, MariaDB, SQL Server, MongoDB, SAP HANA, ClickHouse, Trino, Cassandra, Redis, Valkey and Milvus, and operate the cloud DBaaS estate around them: MySQL HeatWave, Amazon RDS, Aurora, Redshift, Azure SQL Database, BigQuery, Snowflake and Databricks. Every engagement is 24×7, with a 15-minute Severity-1 response.
Operating model
How MinervaDB Consultative Support works
Most enterprises do not run one database; they run ten. Consultative Support from MinervaDB is one engineering partner for all of them, vendor-neutral and measured against production telemetry rather than vendor marketing. The same senior engineer who designs an architecture stays on the rotation that operates it.
Figure 1. From intake to root cause: how every consultative support request is triaged, owned and closed.
One owner
A named principal engineer commands each incident and speaks for MinervaDB to your team, from first response to the written root cause.
Evidence first
Consultative Support starts from the engine’s own telemetry, and every finding cites the metric or system view that justifies it.
Reversible change
Every change carries a verification before, a confirmation gate and a validation after, with the rollback written first.
Coverage
Consultative Support across 12 engines and 8 cloud platforms
Every platform exposes its own evidence. Consultative Support engineers know where each engine records its time, waits and plans, and ask the same four questions everywhere: where time goes, what changed, what the limit is, and what proves the fix.
Figure 2. The first evidence source consultative support engineers read on each platform.
Performance engineering
Query plans, indexing, memory and buffer sizing, storage I/O, connection pooling and workload shaping, focused on the statements that consume most of the database time.
Scalability architecture
Replicas, partitioning and sharding chosen against the real access pattern, with the re-sharding path designed before the first shard exists.
High availability and DR
Clustering, replication and failover per engine, with cross-region backups and quarterly restore and failover drills.
Reliability engineering
SLOs, observability, integrity validation and controlled failure drills that prove the platform before an outage does.
Security and compliance
Encryption, least-privilege access, row and column security and audit trails mapped to GDPR, HIPAA, SOX, PCI DSS and SOC 2.
Operations and automation
Infrastructure as code, reviewed schema migrations, verified backups and capacity forecasting across the estate.
Relational
PostgreSQL, MySQL, MariaDB and SQL Server for the system of record
Relational engines still own the system of record at most enterprises. Consultative Support carries internals depth on all four: planners, storage engines, replication and the HA tooling around them.
PostgreSQL
pg_stat_statements and EXPLAIN analysis, partitioning, autovacuum, logical and physical replication, Patroni HA, and extensions such as TimescaleDB, Citus and pgvector across PostgreSQL 16, 17 and 18.
MySQL
InnoDB tuning, GTID replication, Group Replication and InnoDB Cluster, ProxySQL and MySQL Router, XtraBackup, and upgrades to MySQL 8.4 LTS.
MariaDB
Galera clustering, MaxScale routing, ColumnStore, encryption at rest and migrations from legacy MySQL fleets across MariaDB 10.x and 11.x.
SQL Server
Always On availability groups, Query Store, columnstore, In-Memory OLTP, TDE and migrations to Azure SQL across SQL Server 2019, 2022 and 2025.
SQL · PostgreSQL: partial covering index and plan verification
-- PostgreSQL 16+: partial covering index on the hot window, built without blocking writes.
-- Partial-index predicates must be immutable, so the boundary is a literal that a scheduled job rolls forward.
CREATE INDEX CONCURRENTLY idx_orders_recent_status
ON orders (status, created_at DESC)
INCLUDE (customer_id, total_amount)
WHERE created_at >= DATE '2026-07-01';
-- On a partitioned table: CREATE INDEX ... ON ONLY the parent, build each partition's
-- index CONCURRENTLY, then ALTER INDEX ... ATTACH PARTITION for each one.
-- Verify: expect an Index Only Scan on idx_orders_recent_status and low shared read buffers
EXPLAIN (ANALYZE, BUFFERS, VERBOSE)
SELECT customer_id, SUM(total_amount) AS revenue
FROM orders
WHERE created_at >= DATE '2026-09-01'
AND created_at < DATE '2026-10-01'
AND status = 'shipped'
GROUP BY customer_id
ORDER BY revenue DESC
LIMIT 100;
T-SQL · SQL Server: availability group, Query Store and health check
-- SQL Server 2022+: availability group with two synchronous replicas and one asynchronous DR replica
CREATE AVAILABILITY GROUP ag_appcore_prod
WITH (AUTOMATED_BACKUP_PREFERENCE = SECONDARY, DB_FAILOVER = ON, CLUSTER_TYPE = WSFC)
FOR DATABASE appcore
REPLICA ON
N'SQL-NODE-A' WITH (ENDPOINT_URL = N'TCP://sql-a.corp.internal:5022',
AVAILABILITY_MODE = SYNCHRONOUS_COMMIT, FAILOVER_MODE = AUTOMATIC,
SEEDING_MODE = AUTOMATIC, SECONDARY_ROLE (ALLOW_CONNECTIONS = READ_ONLY)),
N'SQL-NODE-B' WITH (ENDPOINT_URL = N'TCP://sql-b.corp.internal:5022',
AVAILABILITY_MODE = SYNCHRONOUS_COMMIT, FAILOVER_MODE = AUTOMATIC,
SEEDING_MODE = AUTOMATIC, SECONDARY_ROLE (ALLOW_CONNECTIONS = READ_ONLY)),
N'SQL-NODE-C' WITH (ENDPOINT_URL = N'TCP://sql-c.dr.internal:5022',
AVAILABILITY_MODE = ASYNCHRONOUS_COMMIT, FAILOVER_MODE = MANUAL,
SEEDING_MODE = AUTOMATIC, SECONDARY_ROLE (ALLOW_CONNECTIONS = READ_ONLY));
-- Query Store sized so it stays READ_WRITE during incidents (on by default for new databases since 2022)
ALTER DATABASE appcore SET QUERY_STORE = ON
(OPERATION_MODE = READ_WRITE, INTERVAL_LENGTH_MINUTES = 15,
MAX_STORAGE_SIZE_MB = 4096, QUERY_CAPTURE_MODE = AUTO);
-- Verify replica health
SELECT ar.replica_server_name, ars.role_desc, ars.synchronization_health_desc
FROM sys.dm_hadr_availability_replica_states AS ars
JOIN sys.availability_replicas AS ar ON ar.replica_id = ars.replica_id;
Config + SQL · MySQL 8.4: single-primary Group Replication
# my.cnf on every member (MySQL 8.4 LTS); ${...} values are rendered by config management
[mysqld]
server_id = 1 # unique per member
gtid_mode = ON
enforce_gtid_consistency = ON
plugin_load_add = group_replication.so
group_replication_group_name = ${GR_GROUP_UUID}
group_replication_local_address = 10.0.1.11:33061
group_replication_group_seeds = 10.0.1.11:33061,10.0.1.12:33061,10.0.1.13:33061
group_replication_start_on_boot = OFF
group_replication_bootstrap_group = OFF
group_replication_single_primary_mode = ON
-- First member only, once: bootstrap the group
SET GLOBAL group_replication_bootstrap_group = ON;
START GROUP_REPLICATION USER = '${GR_RECOVERY_USER}', PASSWORD = '${GR_RECOVERY_PASSWORD}';
SET GLOBAL group_replication_bootstrap_group = OFF;
-- Every other member: join with the recovery account (placeholders, never literal secrets)
START GROUP_REPLICATION USER = '${GR_RECOVERY_USER}', PASSWORD = '${GR_RECOVERY_PASSWORD}';
-- Verify: three members ONLINE, exactly one PRIMARY
SELECT MEMBER_HOST, MEMBER_PORT, MEMBER_STATE, MEMBER_ROLE, MEMBER_VERSION
FROM performance_schema.replication_group_members;
Group Replication in single-primary mode gives MySQL automated primary election with majority-certified commits. Consultative Support pairs it with MySQL Router or ProxySQL so clients follow the primary through an election. Engine-level depth continues on our PostgreSQL support, MySQL support and SQL Server support pages.
NoSQL and distributed
MongoDB, Cassandra, Redis and Valkey for elastic workloads
Document, wide-column and in-memory stores need a different operating model from relational systems: shard keys instead of indexes alone, consistency levels instead of isolation levels, eviction policy instead of buffer pools. Consultative Support engineers design for those trade-offs explicitly.
MongoDB
Shard-key design, balancer behaviour, oplog sizing, aggregation tuning, write concern and read preference, Atlas operations and upgrades to 7.x and 8.x.
Apache Cassandra
Partition sizing, consistency levels per path, multi-DC replication, compaction strategy, repair scheduling and 4.x and 5.x upgrades.
Redis
Memory and eviction, Sentinel and Cluster failover, RDB and AOF trade-offs, Functions and Streams, and Redis Software operations.
Valkey
The BSD-licensed fork for teams that need a permissive licence: cluster design, Redis-to-Valkey migration and latency engineering.
JavaScript · MongoDB: shard-aligned index and executionStats verification
// MongoDB 7.0+: compound index that matches the shard key prefix and the query shape
db.events.createIndex(
{ tenant_id: 1, event_time: -1, event_type: 1 },
{ name: "tenant_event_time_type_idx" }); // background builds are the default since 4.2
const pipeline = [
{ $match: { tenant_id: ObjectId("66c1a3a2f1b0e5cf3d2a9012"),
event_time: { $gte: ISODate("2026-09-01T00:00:00Z"), $lt: ISODate("2026-10-01T00:00:00Z") },
event_type: { $in: ["purchase", "refund"] } } },
{ $group: { _id: { day: { $dateTrunc: { date: "$event_time", unit: "day" } }, country: "$country" },
revenue: { $sum: "$amount" }, transactions: { $sum: 1 } } },
{ $sort: { "_id.day": -1, revenue: -1 } },
{ $limit: 5000 }
];
// Verify: one targeted shard, IXSCAN on the index, totalDocsExamined close to nReturned
db.events.explain("executionStats").aggregate(pipeline, { hint: "tenant_event_time_type_idx" });
CQL · Cassandra: multi-DC keyspace and bounded time-series partitions
-- Cassandra 4.1+: multi-DC keyspace and a bounded time-series partition
CREATE KEYSPACE IF NOT EXISTS telemetry
WITH replication = {'class': 'NetworkTopologyStrategy', 'dc_us_east': 3, 'dc_eu_west': 3}
AND durable_writes = true;
CREATE TABLE IF NOT EXISTS telemetry.device_metrics (
tenant_id uuid,
device_id uuid,
bucket_hour timestamp,
metric_time timestamp,
metric_name text,
metric_value double,
PRIMARY KEY ((tenant_id, device_id, bucket_hour), metric_time, metric_name)
) WITH CLUSTERING ORDER BY (metric_time DESC, metric_name ASC)
AND compaction = {'class': 'TimeWindowCompactionStrategy',
'compaction_window_unit': 'HOURS', 'compaction_window_size': 1}
AND default_time_to_live = 7776000 -- 90 days
AND gc_grace_seconds = 86400; -- repairs must complete inside this window
-- Reads pinned to the local DC (cqlsh; drivers set this per statement)
CONSISTENCY LOCAL_QUORUM;
-- Repair runs from a scheduler (for example Cassandra Reaper), per DC and within gc_grace_seconds
High availability and DR
Failover mechanics, engine by engine
High availability shortens the gap between failure and recovery; disaster recovery survives the loss of a site. Each engine decides leadership and commits data differently, and that decides the real RPO. Consultative Support documents the mechanism per cluster and proves it in drills.
Figure 3. Who decides leadership, how commits replicate and what consultative support verifies in failover drills on each engine.
Backups follow the same discipline: WAL-G or pgBackRest for PostgreSQL, XtraBackup or MariaBackup for the MySQL family, native backup to URL for SQL Server, backint for SAP HANA and clickhouse-backup for ClickHouse, stored in object storage with object lock so a compromised host cannot rewrite the backup chain.
A backup that has never been restored is a hypothesis. Every consultative support engagement schedules quarterly restore drills, measures the recovery time and recovery point actually achieved, and reports the gap against the agreed objective.
Cloud DBaaS
Managed database services, engineered rather than assumed
Managed services remove host work, not engineering. A noisy neighbour, a surprise bill or a missing feature can still force rework. Consultative Support brings vendor-neutral judgement on when to lean into the managed service and when to engineer around it.
| Platform | What we engineer |
|---|---|
| Amazon RDS and Aurora | Aurora Serverless v2 and I/O-Optimized choices, reader topology, Performance Insights, DMS migrations, IAM and KMS |
| Amazon Redshift | Workload management, concurrency scaling, RA3 sizing, Spectrum, Serverless RPU limits |
| Azure SQL Database | Hyperscale and Business Critical tiers, elastic pools, Always Encrypted with enclaves, Managed Instance migrations |
| Google BigQuery | Editions and reservations, partitioning and clustering, BI Engine, slot and byte cost governance |
| MySQL HeatWave | HTAP offload, Autopilot, vector store, migrations onto HeatWave on OCI, AWS and Azure |
| Snowflake and Databricks | Warehouse sizing, pruning, Snowpipe and Streams; Photon, Delta layout and Unity Catalog governance |
Deeper cloud work runs through our AWS, Azure and Google Cloud data platform engineering pages.
HCL · Terraform: Amazon RDS for MySQL 8.4 with Multi-AZ and managed secrets
# Terraform (AWS provider 5.x): Amazon RDS for MySQL 8.4, Multi-AZ, encrypted, password in Secrets Manager
resource "aws_db_instance" "mysql_primary" {
identifier = "appcore-prod-mysql"
engine = "mysql"
engine_version = var.mysql_engine_version # e.g. "8.4"
instance_class = "db.r7g.2xlarge"
allocated_storage = 2000
max_allocated_storage = 8000
storage_type = "gp3"
iops = 16000
storage_throughput = 750
storage_encrypted = true
kms_key_id = aws_kms_key.rds.arn
db_name = "appcore"
username = var.db_admin_user
manage_master_user_password = true # no password in code or state
multi_az = true
backup_retention_period = 35
deletion_protection = true
performance_insights_enabled = true
performance_insights_retention_period = 31
monitoring_interval = 15
monitoring_role_arn = aws_iam_role.rds_monitoring.arn
enabled_cloudwatch_logs_exports = ["audit", "error", "slowquery"]
vpc_security_group_ids = [aws_security_group.rds.id]
db_subnet_group_name = aws_db_subnet_group.private.name
parameter_group_name = aws_db_parameter_group.mysql84_tuned.name
apply_immediately = false # changes wait for the maintenance window
}
Reliability engineering
Database reliability engineering as a measured loop
Database reliability engineering runs data platforms with the rigour SRE brought to application infrastructure. Consultative Support sets SLOs, instruments every engine, validates integrity on a schedule and rehearses failure, and each stage produces a number the business can see.
Figure 4. The reliability loop and what each drill records in a consultative support engagement.
Observability
Prometheus exporters, Grafana, Datadog or New Relic, fed by engine-native views, in one dashboard that separates symptom from cause.
Integrity validation
Consultative Support schedules amcheck for PostgreSQL, DBCC CHECKDB for SQL Server, validate() for MongoDB and checksum reconciliation between replicas on a fixed cadence.
Controlled failure
Process kills, failovers, partitions and slow-disk drills in pre-production, and in production only where safety nets exist.
Security and migration
Security engineered in, and migrations that keep both sides live
Security is a property of the platform: encryption at rest with KMS, Cloud KMS or Key Vault and in transit with TLS 1.2 or 1.3, least-privilege roles, row and column security, dynamic masking outside production and audit logs shipped to a separate trust boundary. Migrations follow one pattern across engines, shown below.
Figure 5. The migration pattern consultative support applies to cross-engine and cross-platform moves.
Security audits look for privilege creep, dormant accounts, unencrypted backups, weak parameters and exposed superuser endpoints, and feed a remediation backlog ranked by risk. See our database security services for the evidence model.
Test every change, upgrade, failover and migration step in a non-production environment first, keep backups verified by regular restore drills, and maintain a robust disaster-recovery posture with a tested secondary region.
Service portfolio
The consultative support engagements MinervaDB delivers
Engagements are scoped to outcomes, with measurable commitments on response time, resolution path and quarterly platform health.
24×7 production support
Incident response across every engine in the estate, with severity-based targets and principal-engineer incident command.
Performance audits
A two-to-four-week consultative support engagement: a workload baseline, the top statements by cost, a remediation plan and a measured before-and-after report.
Migration engineering
Version upgrades and cross-engine moves such as Oracle to PostgreSQL or on-premises to DBaaS, with reconciliation and rehearsed rollback.
Remote DBA
Fractional or full-time senior DBA capacity through our remote DBA services: monitoring, backups, changes and capacity.
Architecture reviews
Consultative Support delivers the target-state architecture, capacity model, HA and DR design, security posture and a phased plan before you build.
Training and enablement
Consultative Support workshops on engine internals and operations for platform and application teams.
FAQ
MinervaDB Consultative Support FAQ
What customers ask before engaging MinervaDB Consultative Support.
Which database engines does MinervaDB Consultative Support cover?
PostgreSQL, MySQL, MariaDB, SQL Server, MongoDB, SAP HANA, ClickHouse, Trino, Cassandra, Redis, Valkey and Milvus, plus MySQL HeatWave, Amazon RDS, Aurora, Redshift, Azure SQL Database, BigQuery, Snowflake and Databricks.
What are the response targets for 24×7 production support?
Severity 1 in 15 minutes, 24×7×365; Severity 2 in 12 hours; Severity 3 in 24 hours; Severity 4 in 48 hours.
How are ClickHouse engagements delivered?
ClickHouse work is delivered with our sister company ChistaDATA, which specialises in ClickHouse consulting, support and managed services on open-source ClickHouse.
Do you support regulated workloads such as HIPAA, PCI DSS and SOX?
Yes. Engagements routinely operate inside GDPR, HIPAA, SOX, PCI DSS and SOC 2 environments, with encryption, least-privilege access and audit evidence engineered into the platform.
Can MinervaDB lead a cross-engine database migration?
Yes. We run version upgrades and cross-engine migrations with bulk load plus change data capture, reconciliation by row counts and checksums, a shadow period and a gated cutover with a rehearsed rollback path.
Can your engineers work alongside our internal database team?
Yes. Most consultative support engagements complement an internal team, covering nights, weekends, escalations and specialist work such as HA design, audits and migrations.
Are you tied to a database vendor or cloud?
No. MinervaDB is vendor-neutral and does not resell databases or clouds, so recommendations follow the workload, including when the right answer is to keep the current platform.
How do we start?
Book a consultation or email contact@minervadb.com. Most engagements begin with a short assessment of the estate that ranks findings by risk and effort.
Engineer the data tier for the next decade
Talk to a MinervaDB principal engineer about your workload, platform and commitments. MinervaDB Consultative Support: contact@minervadb.com · +1 (844) 588-7287 · +1 (415) 212-6625.