Question 1

How long until this is live?

Accepted Answer

Two weeks for the architecture review and reporting phase, which is where database performance optimization services actually kicks off. Nothing sits idle waiting on us.

Question 2

How do you find the verifiable bottlenecks?

Accepted Answer

We analyze slow query logs directly to identify which particular operations are consuming the most time and server resources.

Question 3

What do we get during the project?

Accepted Answer

A real time optimization dashboard, weekly progress reports, and a dedicated specialist available for questions throughout.

Question 4

What determines pricing for this?

Accepted Answer

Pricing is tiered rather than quoted from scratch, Grow starts things at $1,280, Scale sits at $2,540 once you need everything in Grow, and Accelerate is custom for the enterprise scale version.

Question 5

What industries do you typically serve?

Accepted Answer

Most of our database performance optimization services clients come from manufacturing and logistics operations, multi-location retail and franchise groups, professional services firms, and legal practices handling sensitive records. The work adapts to your industry's particular compliance, terminology, and customer behavior rather than running a generic playbook.

Question 6

Will this cause downtime on our production database?

Accepted Answer

Index changes and query restructuring are tested against a staging copy first, then applied during a scheduled maintenance window. We do not run untested changes directly against a live production database.

Question 7

Do you work with our specific database engine?

Accepted Answer

We work with MySQL, PostgreSQL, and MariaDB. Tell us your engine and version during the initial consultation so the audit accounts for engine specific behavior from the start.

Question 8

What if the slow queries come from our application code, not the database?

Accepted Answer

The slow query log analysis surfaces this distinction directly. If an ORM is generating inefficient queries or an application is making redundant calls, we flag it and hand off clear findings your development team can act on.

Question 9

How do you decide which indexes to add versus remove?

Accepted Answer

We cross reference the slow query log against existing index usage statistics. Indexes that never get used by a verifiable query get flagged for removal since they add write overhead without helping read performance.

Question 10

Can you optimize a database that is already partitioned or replicated?

Accepted Answer

Yes. We review the existing partitioning scheme and replication topology as part of the architecture review and adjust rather than starting over, unless the current setup is actively causing the performance problem.

Question 11

What happens if the audit finds the database itself is not the bottleneck?

Accepted Answer

We tell you directly. If the slow query logs point to network latency, application logic, or infrastructure sizing instead, that finding goes into the audit report so you are not paying to tune a database that was never the problem.

Question 12

Do we need to provide server access, or do you work from logs alone?

Accepted Answer

We need read access to the slow query log and, for configuration tuning, access to the database server itself. We can scope an audit from logs alone first if you want to see findings before granting broader access.

Question 13

How much performance improvement should we expect?

Accepted Answer

It depends on how far the queries and configuration have drifted from what your workload needs. Query restructuring on unindexed tables often produces the largest single gains; configuration tuning and caching build on that.

Question 14

What happens after the two week engagement ends?

Accepted Answer

You get the audit findings, the restructured queries, the tuned configuration, and documentation of what changed and why. Ongoing monitoring or a maintenance retainer is available separately if you want us to keep watching performance after handoff.

Question 15

Do you optimize read heavy and write heavy workloads differently?

Accepted Answer

Yes. A read heavy workload benefits most from indexing, caching, and read replicas. A write heavy workload needs a different balance since aggressive indexing can slow down inserts and updates, so we tune configuration to match your verifiable read to write ratio.

We Fix Slow Queries That Cost You Time and Money