Optimize performance and scale workloads effortlessly with SQL Server database. Overcome resource limitations with instant backups and streamlined performance management, enabling faster and more efficient application development.
Current release — on-premises and cloud
99.99% uptime HA/DR architecture
Execution plans, indexes, SARGable queries
On-premises → Azure with DMA assessment
"Ahex rebuilt our entire SQL Server data layer — reduced query execution time from 18 seconds to 340ms on our most critical reports, eliminated blocking and deadlocks that were taking our application down twice a week, and migrated us to Always On AG with zero-downtime failover. The most impactful database engagement we have ever had."
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Ahex Technologies is your go-to partner for enterprise SQL Server development. With deep expertise in SQL Server schema design, T-SQL optimisation, stored procedures, functions and triggers, Always On Availability Groups, failover cluster instances, database mirroring, log shipping, SSIS ETL pipeline development, SSRS report development, SSAS multidimensional and tabular model development, SQL Server Performance Tuning with Execution Plan analysis, index strategy design, wait statistics analysis, blocking and deadlock resolution, Azure SQL Database migration, Azure SQL Managed Instance, Azure Data Factory, and full SQL Server 2008/2012/2014/2016 modernisation — we deliver SQL Server databases that perform reliably under production load and scale with your application.
Our SQL Server services span the full data lifecycle — from greenfield database design and legacy modernisation to long-term DBA retainers, performance tuning engagements, SSIS/SSRS build-outs, and dedicated SQL Server engineer teams embedded in your organisation. Whether you need a high-availability architecture for a mission-critical application, a poorly performing database tuned to sub-second query times, a SQL Server to Azure SQL migration, or a complex SSIS ETL pipeline connecting your ERP to a data warehouse — our certified database engineers deliver SQL Server solutions that meet your compliance requirements, run reliably under production load, and stay maintainable as your data grows.
Trusted by Walmart, Boeing, Bank of America, and 58% of the Fortune 500 — and the enterprise database of choice for organisations that need deep Microsoft ecosystem integration, mature HA/DR tooling, and a battle-tested relational engine with 30 years of enterprise production history.
From greenfield database design and performance tuning to Always On HA, Azure SQL migration, SSIS ETL pipelines, SSRS reporting, and long-term DBA retainers.
Greenfield SQL Server database design — normalised schema with proper primary keys, foreign keys, and check constraints; index strategy designed alongside the schema; partitioning for large tables; filegroup layout; and collation and compatibility level selection.
Index strategy — clustered, non-clustered, filtered, columnstore, and covering indexes
Table partitioning — range partitioning on date columns for large fact tables
Normalised schema design — 3NF with selective denormalisation for reporting paths
Temporal tables — system-time versioning for audit trails and point-in-time queries
Row-level security and dynamic data masking — data access enforced at the database layer
Systematic SQL Server performance tuning — execution plan analysis, missing index identification, wait statistics review, blocking chain resolution, parameter sniffing fixes, and Query Store baseline comparison. Documented before-and-after query time improvements on every engagement.
Execution plan analysis — scan→seek rewrites, SARGable predicate review
Index strategy — missing indexes via sys.dm_db_missing_index_details, unused index removal
Wait statistics — PAGEIOLATCH, CXPACKET, LCK_M_X wait type root-cause analysis
Blocking and deadlock resolution — deadlock graph analysis, lock escalation tuning
SQL Server HA/DR architecture — Always On Availability Groups with synchronous replication and automatic failover, Failover Cluster Instances on Windows Server Failover Clustering, log shipping for geographically distributed DR, and Azure Site Recovery for hybrid on-premises and cloud DR strategies.
Always On AG — up to 8 readable secondaries, automatic failover, read scale-out
Failover Cluster Instances — shared storage FCI with Windows Server Failover Clustering
Log shipping — geographically distributed warm standby with configurable delay
Backup strategy — full, differential, and transaction log backups with Ola Hallengren scripts
SQL Server Integration Services ETL pipelines — incremental load patterns, slowly changing dimensions, lookup transformations, conditional split, error handling with redirect-and-log, parallel execution, and deployment to SSIS Catalog or Azure-SSIS IR in Azure Data Factory for hybrid cloud ETL.
Incremental load — CDC, watermark, and hash-comparison patterns
Slowly changing dimensions — Type 1, 2, and 3 SCD with SSIS
Azure-SSIS IR — existing SSIS packages lifted to Azure Data Factory without rewrite
Error handling — failed row redirect to error table with source row and error description
SQL Server Reporting Services report development — paginated reports, tablix data regions, drill-down and drill-through reports, subreports, parameterised reports, subscriptions, and rendering in PDF, Excel, Word, and web portal. SSRS integrated with SharePoint and Power BI Report Server.
Paginated reports — tablix, matrix, and chart data regions with grouping and sorting
Parameterised reports — cascading parameters with dependent dataset queries
Report subscriptions — scheduled PDF email delivery with data-driven recipients
React Hook Form + Zod resolver integration
SQL Server to Azure SQL migration — Database Migration Assistant assessment, compatibility level upgrade, BACPAC or Database Migration Service (DMS) migration, post-migration validation, and application connection string cut-over. Azure SQL Managed Instance for near-100% SQL Server compatibility.
DMA assessment — compatibility issues, feature parity gaps, and migration blockers identified
Azure SQL MI — near-100% SQL Server compatibility, SQL Agent, cross-database queries
Azure Database Migration Service — online migration with minimal downtime cut-over
Post-migration validation — query performance baseline comparison on Azure SQL
Ongoing SQL Server DBA retainer — monthly index maintenance, statistics updates, backup verification, blocking and deadlock monitoring, capacity planning, patch assessment, and a named DBA on Slack for P1 production incidents.
Monthly index maintenance — rebuild and reorganise with Ola Hallengren scripts
Backup verification — restore tests to secondary environment monthly
Blocking and deadlock monitoring — Sp_WhoIsActive and custom alert scripts
Named DBA on Slack — P1 production incident response with defined SLA
SQL Server 2008/2012/2014 modernisation to SQL Server 2022 or Azure SQL — compatibility level upgrade, deprecated feature elimination, T-SQL syntax modernisation, SSRS and SSIS version upgrade, and end-of-support risk remediation.
SQL Server 2008/2012 → 2022 in-place or side-by-side upgrade
Deprecated feature removal — SET options, legacy join syntax, old system tables
Compatibility level upgrade — 80→160 with regression testing at each level
End-of-support risk report — CVE exposure and patch gap analysis delivered in 5 days
At Ahex Technologies, we don’t just write code — we own outcomes. From type architecture to post-launch monitoring, our SQL Server DBA team is your end-to-end database partner — responsive, transparent, and accountable.
3–5 days to onboard your dedicated SQL Server DBA engineer
Senior SQL Server DBA — T-SQL, Always On AG, SSIS, SSRS, performance tuning, Azure SQL migration, and full production database managemental types
Direct Slack access to your actual engineer — no account managers
Named, consistent developer — no bait-and-switch
Full code ownership from day one — no lock-in
Timezone-aligned — UK, UAE, and US hours coverage
2-week replacement guarantee if it's not the right fit
The following are the SQL Server security controls, database quality standards, and hardening benchmarks Ahex applies on every engagement — configured before the first production object is deployed.
Every SQL Server engagement Ahex delivers applies the principle of least privilege — dedicated application logins with EXECUTE permission on stored procedures only, never direct table access; separate logins for read and write workloads; SQL Server Audit enabled for privileged login activity; and sa login disabled. No application runs under sysadmin on any Ahex-managed SQL Server. (prev: no implicit any, no unsafe assignments, no unchecked indexed access.
All T-SQL stored procedures use parameterised inputs — never string concatenation into dynamic SQL. When dynamic SQL is required, sp_executesql with typed parameters is used exclusively. SQL injection through the stored procedure layer is structurally prevented on every Ahex SQL Server engagement.
Transparent Data Encryption (TDE) enabled on all production databases — data files and transaction log encrypted at rest using the service master key hierarchy. Backup encryption configured for all SQL Server Agent backup jobs. TDE certificate backed up and stored separately from the database backup files.
Dynamic Data Masking applied to all columns containing PII — email, phone, national ID, and payment card fields masked in query results for non-privileged roles. Row-Level Security policies restrict data access by application user context without application-layer filtering.
SQL Server Agent jobs configured for automated full + differential + transaction log backups with Ola Hallengren's SQL Server Maintenance Solution — the industry standard. Backup files verified with RESTORE VERIFYONLY after every full backup. Recovery time objective tested quarterly with a full restore to a secondary environment.
SQL Server Audit captures all EXECUTE, SELECT, and schema modification events against production databases — audit log shipped to Azure Monitor or a dedicated audit database on a separate SQL Server instance. All DDL changes require a change request number in the deployment script header verified before execution in production.
Our SQL Server engineers design databases that meet regulatory requirements across healthcare, finance, and data privacy — a typed codebase is also an auditable one.
PHI columns encrypted with SQL Server Always Encrypted — column-level encryption where even DBAs cannot read plaintext health record data. TDE encrypts the database file and backup. Row-Level Security policies restrict PHI to authorised clinical roles at the database engine level, separating PHI from non-sensitive data at the type level — misuse flagged at compile time, not discovered in an audit.
Opaque CardNumber and CVV types prevent raw payment strings being passed through un-validated code paths — enforced by the compiler, not just policy.
Dynamic Data Masking applied to all PII columns — email, phone, and national ID fields masked in query results for non-privileged application roles. Row-Level Security restricts which rows each application user context can see, separating PII from anonymised data models — accidental exposure of personal data caught before runtime in production.
Typed event schemas ensure every audit log entry has a known, validated shape — no untyped JSON blobs in the compliance trail.
Cardholder data columns encrypted with SQL Server Always Encrypted — column-level encryption where even DBAs cannot read plaintext card numbers. TDE for data-at-rest, TLS for data-in-transit, column masking for non-cardholder roles. SQL Server Audit captures all access to payment tables. Network segmentation via SQL Server firewall rules.
SQL Server configuration hardened to CIS Benchmark for SQL Server — surface area reduction with sp_configure, sa account disabled, xp_cmdshell disabled, CLR strict security enabled, and SQL Server Browser service disabled where not required. All service accounts run as dedicated low-privilege service accounts, never as SYSTEM or Administrator.
All SQL Server schema changes deployed via numbered migration scripts in version control — reviewed via PR, applied to development and staging before production, and recorded in a deployment log. SSDT schema comparison validates that staging and production schemas match before each release. Rollback scripts maintained alongside every forward migration.
SQL Server connection strings stored in Azure Key Vault or application secrets management — never in appsettings.json committed to source control. Service accounts use Windows Authentication (Kerberos) where possible. SQL Authentication passwords are 24+ character random strings rotated on a defined schedule and managed in the organisation's password vault.
Query performance baselines captured with Query Store before and after every tuning engagement — SLAs defined in terms of P95 query duration, blocking incident frequency, and AG failover RTO. SQL Server Agent alerts configured for blocking chains exceeding 30 seconds, disk space below 20%, and AG health state changes. Baselines revisited quarterly.
From SQL Server 2022 and SSMS to SSIS, SSRS, SSAS, Azure SQL, DMA, SentryOne, and Ola Hallengren scripts — every tool our SQL Server team uses daily on production databases.
SQL Server versions and editions
SQL Server management tooling
SSRS · SSIS · SSAS
Availability and migration tooling
Observability and tuning tooling
SQL Server hardening tooling
ORM and driver integration
Getting typed code to production
We work with all four. We give honest advice — including recommending PostgreSQL for greenfield cloud-native projects with no Microsoft dependency, MySQL for simple web application databases, and Oracle for large enterprises already committed to the Oracle stack.
| Criteria | SQL Server | PostgreSQL | MySQL / Oracle |
|---|---|---|---|
| Windows / .NET integration | Native — Active Directory, Windows Authentication, .NET drivers, SSRS/SSIS/SSAS, Power BI all first-class citizens | Good via ODBC — no native Windows Auth; Kerberos possible but complex | MySQL: basic Windows Auth via plugins; Oracle: native LDAP/AD integration |
| High availability tooling | Best-in-class — Always On AG with automatic failover, readable secondaries, and Azure Arc for hybrid; GUI-driven setup in SSMS | Patroni + etcd or pgpool-II required — more complex setup; no built-in GUI | MySQL: InnoDB Cluster; Oracle: Data Guard — both mature but more complex |
| BI and reporting stack | SSRS for paginated reports, SSAS for OLAP, Power BI native connector — all Microsoft-native, no third-party tooling required | No native BI stack — requires Metabase, Redash, or Grafana | MySQL: no native BI stack; Oracle: OBIEE — powerful but expensive and complex |
| Azure cloud integration | Native — Azure SQL Database, Azure SQL Managed Instance, Azure Arc-enabled SQL Server, Azure Synapse Analytics all extend on-premises SQL Server directly | Good via Azure Database for PostgreSQL — fully managed but a separate product path | MySQL: Azure Database for MySQL; Oracle: Oracle Cloud (not Azure-native) |
| T-SQL vs PL/pgSQL vs PL/SQL | T-SQL — mature window functions, JSON support, temporal tables, columnstore indexes, in-memory OLTP; STRING_AGG, TRIM, APPROX_COUNT_DISTINCT | PL/pgSQL — excellent standards compliance, CTEs are always materialised (Postgres 12+ optimised), JSONB superior to SQL Server JSON | MySQL: limited procedural SQL; Oracle PL/SQL: most powerful procedural SQL, closest to T-SQL for complex logic |
| Ahex recommendation | Best for: Microsoft/.NET organisations, Windows Server environments, organisations using SSIS/SSRS/Power BI, applications requiring Always On AG with GUI management, and Azure-connected architectures | Best for: Linux/cloud-native greenfield projects, JSON/JSONB-heavy workloads, PostGIS geospatial, and cost-conscious open-source deployments | MySQL: simple web applications, WordPress/Magento stacks; Oracle: large enterprises already on Oracle licensing with complex PL/SQL codebases |
| Refactoring safety | Excellent — rename catches all usages | Risky — no static analysis | Good — better than JS, less than TS |
| Production bug reduction | ~40% fewer type-related bugs (strict) | Baseline | ~15% reduction (lenient) |
A SQL Server-specific engagement process — database assessment and performance baseline before any change is made. Architecture and index strategy documented before the first stored procedure is written. All changes applied to development and staging before production. Change management enforced at every phase, zero surprises in prompiler config defined before a single component is built. Safety enforced from sprint zero, not patched in retrospect.
Full SQL Server assessment — sp_Blitz health check, Query Store top query analysis, missing index report from sys.dm_db_missing_index_details, wait statistics baseline from sys.dm_os_wait_stats, disk and memory configuration review, HA/DR architecture review, and SQL Server Agent job audit. Delivered as a written assessment report before engagement work begins.
Database schema design or redesign — entity-relationship model, normalisation decisions, index strategy for identified high-value queries, partitioning plan for large tables, HA/DR topology (Always On AG, FCI, or log shipping), backup strategy design, and filegroup layout. All documented before implementation begins.
Schema objects deployed via numbered migration scripts in SSDT — tables, stored procedures, views, functions, triggers. Index creation. SSIS package development for ETL. SSRS report development. Always On AG or FCI configuration. All applied to development environment and tested before staging.
Performance tuning — execution plan review, index rebuild/reorganise, statistics updates, Query Store forced plan evaluation, parameter sniffing resolution, blocking and deadlock elimination. Security hardening — TDE, audit configuration, row-level security, least privilege login review. Backup and restore test against SLA.
Full schema and data migration to staging. Application integration testing against staging SQL Server. Load test at 2× expected peak concurrent connections. Query performance baseline comparison vs Phase 0 assessment. HA failover test — AG failover confirmed under simulated load. Rollback procedure documented and tested.
SQL Server Agent alerts for blocking, disk space, and AG health. Monthly index maintenance and statistics updates via Ola Hallengren scripts. Quarterly backup restore test. Query Store performance regression monitoring. Named DBA on Slack for P1 production incidents. Monthly performance report delivered to client.
All models include database assessment report, SSDT schema versioning, change management documentation, HA/DR architecture, security hardening, named DBA engineers, and full ownership from day one.
Cost is locked in a fixed-scope model. Ideal when the roadmap is well-defined and you want budget certainty.
Billing
Best For
A dedicated pod you optimise, scale, and augment your in-house team with. Best for ongoing product development.
Best suited for teams that need predictable sprint velocity.
Billing
Best For
Model Fit
In this model, there is no fixed time or budget. You will pay for the actual hours worked or materials completed and used.
Billing
Best For
Your teams will ship faster, safer code — and your production systems will have fewer database incidents and significantly faster query times — when SQL Server is designed and maintained correctly from the start.
Ahex starts every SQL Server engagement with a full database assessment: sp_Blitz health check, Query Store top query report, wait statistics baseline, missing index analysis, and HA/DR architecture review. Every recommendation is backed by query execution data and wait statistics — not guesswork. Clients receive a written assessment report before any development work begins.
Ahex enforces stored procedure architecture on every SQL Server engagement — all data access goes through parameterised stored procedures, never ad-hoc T-SQL from the application layer. Business logic stays in the database, is version-controlled in SSDT, and is tested independently of the application. SQL injection through the data access layer is structurally prevented.
All SQL Server schema changes deployed via numbered SSDT migration scripts committed to Git — reviewed in a PR, applied to development then staging, and recorded in a deployment log. No more "someone changed a column in production directly." Schema drift between development, staging, and production is eliminated. The SSDT project is the authoritative database schema.
Ahex configures Always On Availability Groups on every SQL Server engagement requiring HA. Index rebuilds and DBCC CHECKDB run against a secondary replica — production is never taken offline for maintenance. Automatic failover with sub-30-second RTO means planned maintenance windows are rarely required. Secondary replicas offload read-heavy reporting workloads, freeing the primary for transactional traffic.
Ahex captures Query Store baselines before and after every performance tuning engagement — P95 query duration, execution count, and total CPU time per query plan are documented before the first index is created. After tuning, the same metrics are captured and delivered in a before/after performance report. Every client sees exactly how much faster their queries run.
Ahex configures three independent data protection layers on every SQL Server engagement touching sensitive data: Transparent Data Encryption for data-at-rest encryption of all database files and backups, Always Encrypted for column-level encryption of the most sensitive fields (even DBAs cannot read plaintext), and Row-Level Security policies that restrict which rows are visible to each application role — enforced at the database engine level, not the application layer.
Ahex deploys Ola Hallengren's SQL Server Maintenance Solution on every managed SQL Server — the industry-standard open-source maintenance framework used by thousands of production SQL Server instances worldwide. Index rebuild and reorganise jobs run on a fragmentation-based schedule. Statistics update jobs run nightly. Backup jobs run with integrity checks and backup compression. Maintenance job history retained and monitored.
Ahex has delivered SQL Server engagements for clients in the UK, UAE, USA, and Australia across financial services, healthcare, manufacturing, logistics, and enterprise SaaS. Our SQL Server engineers work in IST timezone with 4–6 hour overlap with UK and UAE business hours — assessment reviews, architecture calls, and P1 production incident response all happen in your working hours.
Our SQL Server engineers use AI-powered tools across every phase — from type migration to test generation — without sacrificing type safety or code quality. The result: more output, fewer delays, the same rigorous strictness.
AI generates Zod schemas from JSON samples, infers types from existing JS, and suggests typed replacements for any casts — saving 2–3 days per migration sprint.
AI-assisted code review flags unsafe type patterns, missing return types, and any-cast misuse before human review — fewer back-and-forth cycles and faster PR merges.
T-SQL stored procedure generation, index recommendation analysis, and ETL packages auto-generated from Zod schemas and function signatures — QA phase starts with strong coverage.
Combined AI acceleration across all phases consistently cuts total delivery timelines by 25–35% without scope compromise.
T-SQL stored procedure and query generation from business requirements, index recommendation review, execution plan interpretation, and SSRS report expression generation. Every Ahex SQL Server engineer uses GitHub Copilot with SQL Server T-SQL context — all AI-generated T-SQL is reviewed, tested against the Query Store baseline, and verified in development before deploying to staging.
AI accelerates SSIS package structure generation from ETL specification documents, SSRS report layout scaffolding from report requirements, and T-SQL migration script generation from SSDT schema comparison output — 50% of boilerplate development produced before implementation sprint, reviewed by a senior SQL Server engineer on every project.
Database assessment reports, stored procedure documentation, index strategy rationale, HA/DR architecture documentation, and DBA runbooks auto-generated from SQL Server system catalog queries and Query Store data — always in sync with the actual production database state.
AI-assisted execution plan analysis — query plan XML interpreted to surface scan-to-seek opportunities, missing predicate indexes, and parameter sniffing patterns with T-SQL fix suggestions. SQL Server engineers verify every recommendation against the Query Store before implementing in development. Shift-left performance on every SQL Server project.
All AI-generated T-SQL stored procedures, SSIS package structures, and index recommendations are reviewed, tested in development, and owned by a named Ahex SQL Server Ahex engineer before it ships. We use AI to move faster — not to skip the assessment phase, bypass the staging validation requirement, or deploy schema changes directly to production without a numbered migration script.
Every team running SQL Server in production hits these sooner or later. These are the problems our engineers diagnose repeatedly and know how to prevent from sprint zero.
Problem
An enterprise SaaS application's dashboard page takes 18 seconds to load. SQL Server Profiler shows a single stored procedure making a 42-second logical read scan on a 28-million row Orders table. The WHERE clause filters on OrderDate and CustomerID — but the clustered index is on OrderID, and there is no non-clustered index covering those columns. The query scan reads all 28 million rows on every dashboard load.
Solution
Ahex analyses the execution plan — the table scan is confirmed via the Actual Execution Plan with 28.4M rows estimated and actual. A composite non-clustered index on (CustomerID, OrderDate) INCLUDE (OrderTotal, OrderStatus) is created. The execution plan changes from a table scan to an index seek with a key lookup eliminated by the INCLUDE columns. Query execution drops from 42 seconds to 340ms. Dashboard page load drops from 18 seconds to under 1 second. The index is deployed during a low-traffic window with ONLINE=ON — zero application downtime.
Problem
A .NET application connected to SQL Server experiences timeout errors twice a week — typically during peak usage (9–11am). sp_WhoIsActive shows blocking chains of 15–20 sessions with a single head blocker holding a shared lock on the Inventory table for 45+ seconds. Deadlock graphs in the SQL Server error log show circular lock dependencies between two stored procedures updating Order and OrderLine in opposite orders.
Solution
Ahex analyses the deadlock graph XML and blocking chain — the head blocker is a long-running SELECT with NOLOCK hints missing. The deadlock is resolved by enforcing consistent object access order in both stored procedures (always Order before OrderLine) and wrapping updates in the shortest possible transactions. READ_COMMITTED_SNAPSHOT isolation is enabled at the database level — readers no longer block writers. After the fix: zero blocking incidents and zero deadlocks across the following 30 days of monitoring.
Problem
A manufacturing company is running SQL Server 2012 (end of extended support: July 2022). The DBA team has identified 14 unpatched CVEs against the SQL Server engine and OS. The security team flags the database server in monthly vulnerability scans. The application vendor requires SQL Server 2016+ for the next major release. An in-place upgrade has been attempted twice and rolled back due to compatibility errors in stored procedures using deprecated syntax.
Solution
Ahex performs a side-by-side migration — a new SQL Server 2022 instance is provisioned alongside the existing 2012 instance. Database compatibility level is upgraded incrementally (100→110→130→160) with query regression testing at each level using Query Store. Deprecated T-SQL syntax identified by the Database Migration Assistant is refactored before migration. Log shipping replicates data to the new instance in near-real-time. Cutover is a 4-minute maintenance window. All 14 CVEs are resolved and the application vendor upgrade proceeds.
Problem
A SQL Server database has no scheduled index maintenance. sys.dm_db_index_physical_stats shows average fragmentation of 87% across the 15 most-queried tables. Statistics were last updated 6 months ago. Query performance has been degrading gradually — queries that previously ran in 200ms now take 3–4 seconds. The team is unaware that fragmentation is the root cause and have been adding hardware instead.
Solution
Ahex deploys Ola Hallengren's IndexOptimize and UpdateStatistics SQL Server Agent jobs — index reorganise for 10–30% fragmentation, index rebuild with ONLINE=ON for over 30% fragmentation, and full statistics update nightly. After the first maintenance run, average fragmentation drops from 87% to 2.1%. Query times return to baseline within 24 hours. SQL Server Agent email alerts are configured to notify the DBA team if any maintenance job fails.
Problem
An enterprise application has an Always On Availability Group configured but has never been tested under realistic conditions. A simulated failover during a maintenance window takes 8 minutes for the secondary to come online and the application to reconnect — against a 2-minute RTO SLA. The AG listener connection string is not configured in the application, so developers must manually update the database server name in the config file during a real failover.
Solution
Ahex performs a full AG health review — the 8-minute failover is caused by the secondary having a 4-minute redo queue from a log shipping delay and the application not using the AG listener DNS name. Ahex reconfigures the AG for synchronous commit on the primary secondary pair (eliminating the redo queue lag), updates the application connection string to use the AG listener, and configures MultiSubnetFailover=True in the connection string for sub-30-second client reconnection. Tested failover time drops from 8 minutes to 22 seconds — inside the 2-minute RTO SLA.
Problem
A SQL Server database has no schema version control. Schema changes are made directly in production using SSMS — tables are altered, columns are added, stored procedures are modified without any review or documentation. When a column rename breaks three stored procedures and causes application 500 errors, the DBA cannot determine what changed, when it changed, or who changed it. A rollback requires recreating the stored procedures from memory.
Solution
Ahex introduces SSDT (SQL Server Data Tools) schema versioning — the entire database schema is imported into an SSDT project in Git. All subsequent schema changes are made as numbered migration scripts, reviewed via PR, applied to development and staging before production, and recorded in a deployment log. DDL Triggers are added to capture any direct production schema changes to an audit table. Within four weeks, the team has full schema history, a one-command rollback for any migration, and zero direct production DDL changes.
Six solution types where our SQL Server engineers have deep, repeated delivery experience — every stack listed is what we shipped in production in the last 18 months.
Greenfield SQL Server database design for enterprise applications — normalised schema, index strategy, stored procedure architecture, row-level security, TDE, Always On AG, and SSDT version control. SPAs with strict tsconfig, generics-first component design, typed state management (NgRx / Zustand), and Zod-validated API layers across the UI.
Fully typed REST and GraphQL APIs with NestJS dependency injection, Prisma typed models, Zod request validation middleware, and tRPC for end-to-end type safety.
Multi-package monorepos with shared @company/types, shared tsconfig bases, ESLint boundary rules, and Nx affected builds that cut CI time by ~60%.
Zero-risk migrations using allowJs incremental strategy, type-coverage audits, any-elimination phases, and strict mode graduation — production stays deployable throughout.
AWS Lambda and Vercel SSIS ETL pipelines from SAP, Oracle, and flat file sources; SSRS paginated reports; SSAS tabular and multidimensional models — delivered alongside the SQL Server database. Zod-validated payloads, and cold-start optimised bundles under 1MB.
On-premises SQL Server migrated to Azure SQL Database or Azure SQL Managed Instance — DMA assessment, compatibility remediation, DMS migration, and post-migration performance baseline with shared types in a monorepo, single CI/CD pipeline, tRPC or OpenAPI contracts, and one team owning the entire stack from DB to UI.
The following are the industry standards and compliance that we align SQL Server with. Our team ensures that these are built into the markup from sprint one only.
AI accessibility scanning flags WCAG violations in real time during development — not post-launch in an audit.
Section 508 for the USA. An U.S. federal accessibility standard that requires government agencies and their digital services to be accessible to people with disabilities.
A U.S. civil rights law. It promotes the idea that people with disabilities should also have equal access. Its web accessibility requirements encourage businesses to provide inclusive online experiences.
Standards that help websites collect user data transparently. Supports GDPR and CCPA. Gives users control over their data.
W3C SQL Server Validation ensures that the SQL Server development follows official web standards. It must improve compatibility with browsers, reliability, and overall user experience.
Standardized format that helps search engines understand content on the webpages. Improves SEO and crawlability.
We deliver SQL Server database solutions for enterprise organisations across all major verticals — from healthcare typed APIs to fintech platforms, logistics systems to SaaS products. Click an industry to explore what we've delivered.
Our solutions for healthcare and fitness focus on developing user-friendly interfaces for fitness apps, appointment scheduling systems, and health tracking platforms, ensuring secure and efficient data management.
We help real estate companies build immersive property listings, interactive maps, and responsive websites that streamline property searches and improve customer engagement.
Our front end services help automotive and manufacturing companies build robust applications for managing inventory, tracking production, and enhancing customer engagement through intuitive interfaces.
We deliver secure and compliant front-end solutions for financial institutions, enhancing user experience through intuitive dashboards, transaction management systems, and mobile banking apps.
Our frontend development services for tourism and hospitality focus on creating interactive maps, virtual tours, and streamlined booking interfaces that enhance the customer journey from discovery to booking.
We help media and entertainment companies build intuitive systems for content delivery and consumption, including real-time single-page applications and personalized content recommendations that keep audiences engaged.
Our expertise extends to creating modern, scalable front-ends for software applications, ensuring fast performance, intuitive navigation, and seamless integration with backend systems.
We empower e-commerce platforms with seamless checkout processes, intuitive product navigation, and responsive designs that boost sales and customer satisfaction.
Our front-end services for education include developing interactive learning platforms, online course management systems, and student portals that enhance engagement and accessibility.
Known for building innovative technology solutions across diverse industries, we’ve received multiple awards and recognitions from top B2B platforms.
Clutch 1000 Company – 2025
Recognized by Clutch among the top 1000 global companies for excellence in service and delivery in 2025
Clutch Global Award Winner – Fall 2024
Awarded by Clutch as a Global Leader for outstanding performance and client satisfaction in Fall 2024
Clutch Global Award Winner – Spring 2024
Recognized by Clutch as a Global Leader for delivering high-quality solutions and consistent client success in Spring 2024
Clutch Champion – Fall 2024
Honored by Clutch as a Champion for sustained excellence, industry leadership, and exceptional client feedback in Fall 2024
Clutch Champion – Spring 2024
Honored by Clutch as a Champion for sustained excellence, industry leadership, and exceptional client feedback in Fall 2024
Ahex Technologies Pvt. Ltd. developed a client-facing mobile app with geolocation features as well as an intranet portal for employees. They provide ongoing support for any updates that need to be made.
An enterprise-grade AI Voice Assistant platform designed to automate, govern, and optimize every guest interaction across single and multi-property hotel environments.
Southwest Funding is a Dallas-based mortgage lender founded in 1993 — serving 50,000+ home loans across 29 states with Conventional, FHA, VA, and USDA programs through 1,200+ licensed loan officers.
Book a free scoping call with a senior SQL Server DBA engineer. We'll review your current SQL Server version, instance configuration, HA/DR architecture, performance pain points, and Azure migration requirements — and give you an honest assessment of what a performance tuning engagement, version modernisation, or DBA retainer would deliver.
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Build flexible and scalable applications with MongoDB's document-oriented database architecture. Ahex provides MongoDB consulting, development, integration, deployment, performance optimization, and dedicated support for distributed and high-volume data environments.
Build secure, reliable, and high-performance applications with PostgreSQL. Ahex provides PostgreSQL development, database administration, monitoring, performance optimization, migration, and ongoing support for scalable data-driven applications.
Yes — it’s the explicit choice of enterprise engineering teams at Use SQL Server if your organisation is a Microsoft/.NET shop, you need Always On AG with GUI management, you use SSIS/SSRS/Power BI, or you are deploying to Azure with Azure SQL MI. Use PostgreSQL for Linux/cloud-native greenfield projects with no Microsoft dependency — especially if PostGIS or JSONB is a core requirement. For most .NET enterprise applications, SQL Server’s deep ecosystem integration makes it the natural choice. Microsoft’s strict mode, shared types, and IDE tooling make large multi-team codebases safe to refactor and extend. For smaller utility scripts plain JavaScript may be fine, but anything long-lived and multi-year SQL Server estates benefit enormously from proper DBA oversight.
Any project with more than one developer, more than a few weeks of lifetime, or Assessment first — sp_Blitz health check, Query Store top query analysis, wait statistics baseline, and execution plan review before any index is created or T-SQL is rewritten. Every recommendation is backed by measured query data. Prisma, tRPC, and Next.js — it’s the natural choice for the modern JavaScript ecosystem rather than an add-on.
We configure a CI type-check gate (tsc –noEmit) that blocks any PR introducing type errors, activate @typescript-eslint/no-explicit-any and @typescript-eslint/ban-ts-comment to prevent suppressions, and run a type-coverage threshold check on every build. Strictness is enforced by the CI pipeline, not by convention or code review alone.
By default, yes — strict:true enables strictNullChecks, noImplicitAny, strictFunctionTypes, and several other critical checks simultaneously. If you have a legacy codebase where strict mode can’t be enabled immediately, we use an incremental approach — enabling individual flags one at a time and graduating to full strict over sprints.
Typically 3–12 weeks depending on codebase size, existing test coverage, and strictness targets. We use an incremental allowJs strategy — your project stays deployable throughout, never blocked on a big-bang branch. Most production codebases see zero runtime regressions after our migration.
We start with a discovery call to understand your SQL Server version, instance size, application stack, HA requirements, and primary pain points. We then propose an engagement model — fixed budget, dedicated team, or time & material — and move into type architecture design, iterative build or migration sprints, and a documented handover with type coverage report.
Absolutely. Yes — we regularly take over SQL Server environments from other teams or outgoing DBAs. We start with a full sp_Blitz health check, Query Store review, backup verification, HA/DR architecture audit, security audit (CIS Benchmark), and SQL Server Agent job review. Missing Zod boundaries, and ESLint rule gaps — produce a prioritised remediation roadmap, and execute it incrementally without pausing delivery.
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