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To start a SQL Server engagement
Scoping through first sprint
100%
Senior engineers, US-based
No offshore handoff on production databases
Every sprint
Working software on a preview URL
Not a status deck between milestones
100%
Schema and infrastructure you own
In your own environment, from the first commit
Where SQL Server fits
Editions, deployment models, and the decision inside each
SQL Server isn't one product — it's a family of editions and deployment models, and picking the wrong one is either an overspend or a ceiling you hit sooner than expected.
Standard vs. Enterprise edition
Standard Edition covers most workloads — core relational database engine, basic high availability, standard reporting. Enterprise Edition adds features like advanced Always On configurations, table and index partitioning at scale, and higher resource limits. The gap between them is real and worth evaluating against your actual scale before assuming you need the larger edition.
On-premises vs. Azure SQL Database vs. Azure SQL Managed Instance
On-premises SQL Server gives full control over version, configuration, and hardware. Azure SQL Database is a fully managed, serverless-capable option that abstracts away the underlying instance entirely. Azure SQL Managed Instance sits between the two — near-complete SQL Server compatibility with Azure handling patching and backups. The right one depends on how much operational control you actually need versus want to hand off.
T-SQL is the layer that doesn't change across any of them
Transact-SQL is SQL Server's query language across every edition and deployment model, which is what makes migration between on-premises and Azure SQL more mechanical than migrating to a different database engine entirely — most application code doesn't need to change, even when the infrastructure underneath does.
SSIS, SSRS, and SSAS are still widely deployed, and worth evaluating honestly
SQL Server Integration Services (ETL), Reporting Services (reports), and Analysis Services (OLAP and tabular models) remain in production at a large share of existing SQL Server shops. They're not necessarily what a new build should start with — modern alternatives often fit a greenfield project better — but ripping them out of a working system for their own sake is rarely the right call either.
Columnstore indexes for analytical workloads
A columnstore index reorganizes data by column rather than row, and it can dramatically speed up aggregation-heavy analytical queries over large tables without moving the data to a separate warehouse. This is one of the more underused features in SQL Server deployments still structured entirely around row-store indexes.
In-memory OLTP for the transactions that need it
SQL Server's memory-optimized tables remove locking and latching overhead for high-throughput transactional workloads — a real option for a specific class of performance problem, and unnecessary complexity for a workload that isn't actually contention-bound.
Architecture decisions
What's expensive to unwind after a SQL Server system is live
The decisions below are inexpensive to make well from the start and genuinely disruptive to fix once applications and reports have been built around the gaps.
Indexing strategy driven by actual query plans
An index added because a table "felt slow" without checking the execution plan first is as likely to hurt write performance as it is to help reads. Reviewing actual query plans — and removing indexes nothing uses, which every mature database accumulates — is routine maintenance that pays for itself.
Normalization decided deliberately, not defaulted
A fully normalized schema minimizes redundancy and update anomalies; a deliberately denormalized one trades that for read performance on specific, known query patterns. The mistake is denormalizing by accident, incrementally, without ever deciding to — that's how a schema ends up inconsistent instead of fast.
High availability tested with a real failover
Always On availability groups and failover clustering are easy to configure and easy to assume are working. The gap that actually costs downtime is never having triggered a real failover — a scheduled drill is the only way to know the automatic failover, and the application's reconnection logic, both behave the way the runbook assumes.
Backup strategy matched to actual recovery requirements
Full, differential, and transaction log backups each serve a different recovery point objective, and the right combination depends on how much data loss is actually acceptable — a decision worth making explicitly rather than inheriting whatever the default maintenance plan happened to set up.
Row-level security and Always Encrypted, where the data warrants it
SQL Server's row-level security and Always Encrypted features let sensitive data stay protected even from users with broad query access, including database administrators in the Always Encrypted case. Designing this in for regulated data from the start avoids a much larger retrofit once the schema and application queries are already built around plaintext access.
Statistics and maintenance jobs kept current
Query plan quality depends on SQL Server's statistics staying up to date, and a maintenance plan that stops running — quietly, because nobody's watching it — degrades performance gradually enough that it's often blamed on load growth instead of the actual cause.
What's involved
SQL Server engagement types
What moves the scope is schema complexity, current performance problems, and whether the goal is a new system, a migration, or fixing an existing database's reliability.
| Engagement | Commitment | Timeline | What's included |
|---|---|---|---|
| Database and performance audit | Fixed scope | 1 – 3 weeks | Query plan and indexing review, high-availability configuration assessment, and a prioritized list of what's actually causing slow queries or risk. |
| Schema design and build | Fixed scope | 4 – 10 weeks | New schema designed around real application query patterns, with indexing, constraints, and a tested backup and recovery strategy. |
| High-availability implementation | Fixed scope | 3 – 8 weeks | Always On availability groups or failover clustering configured and validated with an actual failover drill, not just deployed and assumed working. |
| Migration to or off SQL Server | Fixed scope | 6 – 16 weeks | Migration to Azure SQL Database or Managed Instance, or off SQL Server to Postgres, including the data-type and query translation work either direction requires. |
| Ongoing database support | Ongoing retainer | Ongoing | Standing ownership of performance tuning, patching, and backup verification through the next scale threshold and the next audit. |
Ranges assume US-based senior engineers and include a tested failover or restore drill, which a cheaper quote often skips in favor of a configuration nobody has actually exercised. The audit exists as its own first step because a query-plan review usually finds the real bottleneck before anyone commits to a larger scope.
Migration
Moving onto SQL Server, onto Azure SQL, or off SQL Server entirely
All three are real, common requests, and the decision usually turns on licensing model, existing team expertise, and how deeply an application depends on T-SQL-specific features.
Onto SQL Server, from another engine
Usually driven by an organization standardizing on the Microsoft stack, or acquiring a system built on SQL Server and needing to integrate it. The migration work centers on translating the source engine's SQL dialect and data types into T-SQL's equivalents, which is rarely a 1:1 mapping.
Onto Azure SQL, from on-premises SQL Server
The most mechanical of these three, because the target still speaks T-SQL. Azure Migrate assesses the source database first, and the main decision is Azure SQL Database versus Managed Instance versus a lift-and-shift SQL Server VM, based on how much operational control you're willing to give up.
Off SQL Server, to Postgres
A real and increasingly common request, usually driven by licensing costs relative to the workload rather than a technical limitation of SQL Server itself. The actual work is translating T-SQL-specific syntax and stored procedures, since PostgreSQL's SQL dialect and procedural language differ from T-SQL in ways that don't translate mechanically.
Stored procedures are usually the hardest part of any direction
Business logic embedded in T-SQL stored procedures is the part of a SQL Server migration that resists automated tooling the most. Assessing how much logic actually lives in the database layer — versus the application layer — early in scoping is what turns a migration estimate from a guess into a real number.
SSRS and SSIS dependencies need their own migration plan
A migration that moves the database but leaves SQL Server Reporting Services or Integration Services jobs pointed at the old system isn't finished — those dependencies need an explicit plan, whether that's migrating them too or replacing them with a different reporting or ETL tool.
Downtime tolerance shapes the whole approach
A migration that can tolerate a maintenance window is a meaningfully simpler project than one that needs near-zero downtime, which requires ongoing replication and a carefully sequenced cutover. Deciding this explicitly, early, avoids overbuilding a migration path the business didn't actually need.
SQL Server vs. the alternatives
When SQL Server is the right database, and when it isn't
SQL Server is a mature, capable relational database. It's not automatically the right choice for every relational workload, and the decision should be made on real factors, not inertia.
Where SQL Server's ecosystem fit is real
A team already running .NET applications, Windows Server infrastructure, and Active Directory gets genuine value from SQL Server's tooling integration — SSMS, Visual Studio's native tooling, and Azure's direct migration path. This is the same ecosystem argument that applies to Azure generally.
Where Postgres is increasingly the default
For a team without an existing Microsoft footprint, PostgreSQL offers a comparably capable relational database with a fully open-source license and no per-core licensing model to plan around. This is a large part of why migrating off SQL Server has become a common request rather than a rare one.
Licensing complexity is a real cost driver, even without a dollar figure attached
SQL Server's per-core and CAL-based licensing models add real planning overhead that a simpler open-source database doesn't carry — the complexity itself, independent of any specific number, is often what pushes a team to evaluate alternatives.
High-availability maturity favors SQL Server for some regulated workloads
Always On availability groups and the broader SQL Server high-availability tooling are mature and well-documented, which matters for regulated industries with strict uptime and audit requirements where the operational familiarity is itself a risk-reduction factor.
The migration decision should follow the workload, not a general preference
"We should move off SQL Server" and "we should move onto it" are both sometimes right and sometimes the more expensive path dressed up as a modernization project. We'll assess your specific application's dependency on T-SQL-specific features before recommending either direction.
Hiring
What to look for when hiring a SQL Server developer
Someone who can write a query is different from someone who's tuned an execution plan on a table with real production volume, or configured a failover that actually failed over correctly.
Execution plan literacy
Ask a candidate to walk through how they'd diagnose a slow query — the answer should involve reading an actual execution plan, not just adding an index and hoping. This is the skill that separates real tuning from guesswork.
High-availability configuration and testing experience
Someone who's configured Always On availability groups and also tested a real failover is a different level of experience than someone who's only read the documentation. Ask specifically whether they've triggered one in a non-production environment.
T-SQL and stored procedure fluency, if your system uses them
If business logic lives in stored procedures, confirm the candidate is comfortable reading and modifying T-SQL procedural code, not just writing application-layer queries against the database.
Migration experience in the direction you actually need
Migrating onto Azure SQL and migrating off SQL Server to Postgres are different skill sets. Ask about the specific direction relevant to your project rather than "database migration experience" in general.
Comfort recommending against SQL Server
The engineers worth hiring will tell you honestly when Postgres fits your situation better, instead of defaulting to the database they're most comfortable with regardless of your actual constraints.
Related
Related services
What SQL Server work usually connects to.
Questions
Common questions about SQL Server development
What teams ask before a first call.
A database and performance audit is the smallest engagement here, and a schema build or migration is a larger one. An ongoing support retainer is priced to the environment rather than sold as a fixed headcount.
What moves the number most is schema complexity, how much business logic lives in stored procedures, and whether a migration is involved. The audit exists to answer that before the rest gets quoted, and it often finds that the real bottleneck is a missing index rather than something that needs a full rebuild.
Designs schemas and indexes around the queries an application actually runs, tunes performance using real execution plans rather than guesswork, and configures high availability — Always On availability groups or failover clustering — in a way that's actually been tested with a real failover.
A good SQL Server developer also handles the parts that don't show up until something goes wrong: a backup strategy matched to real recovery requirements, and statistics maintenance that keeps query plans accurate as data grows.
If your organization already runs on .NET, Windows Server, and Active Directory, SQL Server's tooling integration is a genuine advantage. If there's no existing Microsoft footprint, PostgreSQL is an increasingly common default — comparably capable, fully open source, with no per-core licensing model to plan around.
Licensing complexity, independent of any specific figure, is a real factor a lot of teams weigh here, and it's a large part of why migrating off SQL Server has become a common request rather than a rare one. We'll assess your specific application's dependency on T-SQL-specific features before recommending either direction.
The main work is translating T-SQL-specific syntax and stored procedures into the target database's dialect, since business logic embedded in stored procedures is usually the part that resists automated migration tooling. We assess early how much logic lives in the database layer versus the application layer, because that ratio is what actually determines the real timeline.
We also plan explicitly for any SSRS or SSIS dependencies pointed at the old database — a migration that moves the data but leaves reporting or ETL jobs behind isn't actually finished.
Azure SQL Database is fully managed and abstracts away the underlying instance almost entirely, including a serverless billing option that scales down to near zero during idle periods. Azure SQL Managed Instance sits closer to on-premises SQL Server in terms of feature compatibility and operational control, while Azure still handles patching and backups.
The right one depends on how much SQL Server-specific compatibility your application actually needs versus how much operational control you're willing to hand to Azure.
By testing it. Always On availability groups and failover clustering are straightforward to configure and easy to assume are working correctly — the failure mode that actually costs downtime is discovering during a real outage that the automatic failover, or the application's reconnection logic, doesn't behave the way the runbook assumed.
A scheduled failover drill in a non-production environment is the only way to know for certain, and it's a routine part of how we validate any high-availability build.
Standard Edition covers most workloads well — the core relational engine, basic high availability, and standard reporting. Enterprise Edition's additional features, like advanced Always On configurations and table partitioning at large scale, matter at a specific scale and workload profile that not every project has reached.
We'll evaluate your actual requirements against the real feature gap rather than defaulting to the larger edition because it sounds safer.
Yes — SQL Server Integration Services, Reporting Services, and Analysis Services remain in production across a large share of existing SQL Server deployments, and they're often not worth ripping out of a working system for their own sake. We'll work within them where that's the pragmatic choice, and recommend a modern alternative when a specific project genuinely calls for one.