BigQuery is a serverless analytics platform, so there are no clusters to size or manage. Snowflake and Databricks take different approaches to compute, engineering and AI workloads. The right choice depends on your data, workloads, existing technology and how much infrastructure control you need.
Unlock your data’s potential on Google Cloud
From BigQuery and AlloyDB to Vertex AI and managed operations, Ardent’s Google Cloud engineers help organisations build governed data platforms for reliable reporting, automation and production AI.
TRUST AND PROOF POINTS
Since 2008
Engineering and operating data platforms for organisations worldwide.
Google Cloud partner
Engineering capability across Google Cloud data and AI technologies.
2m+ hours
Engineering delivered across data and software projects.
ISO 27001
Information security supported by independently certified processes.
WHY GOOGLE CLOUD
Integrated data, analytics and AI at scale
Google Cloud brings data warehousing, databases, engineering and AI into one connected ecosystem. BigQuery provides serverless analytics without clusters to size, while AlloyDB and Bigtable support relational and high-scale operational workloads.
That foundation extends into AI through Vertex AI and Vertex AI Search, allowing organisations to build search, retrieval and AI applications against governed enterprise data rather than creating another disconnected data layer.
Ardent brings the engineering underneath it together, data preparation, pipelines, governance, quality and cost optimisation, choosing the right combination of Google Cloud services around the workload rather than forcing every requirement into one product.
✓
Serverless analytics with BigQuery
✓
Relational and high-scale data services
✓
AI and search with Vertex AI
✓
Built for cloud-native innovation
✓
Integrated data engineering and governance
WHAT WE DELIVER
Google Cloud expertise for real business outcomes
Our Google Cloud capability spans databases, data engineering, analytics, AI and ongoing operations, helping you build the right environment for each workload.
Data warehousing & analytics
Design governed BigQuery environments with partitioning, clustering and query optimisation for faster reporting, scalable performance and better cost control.
Relational databases
Run PostgreSQL-compatible transactional workloads on AlloyDB and Cloud SQL, combining familiar SQL with managed reliability and cloud-scale performance.
NoSQL & high-scale data
Build low-latency, high-throughput services on Bigtable for application and time-series workloads that need reliable performance as data volumes and demand grow.
AI-powered search
Build vector search and retrieval with Vertex AI Search, grounding RAG and AI applications in governed Google Cloud data your organisation can trust.
Data engineering & pipelines
Build automated pipelines with Dataflow, Dataproc, Pub/Sub and Dataform, moving data reliably while catching quality issues before they reach reporting or AI.
Generative AI & machine learning
Use Vertex AI and BigQuery AI capabilities to build RAG, foundation-model and machine-learning workloads directly on governed enterprise data.
BI & reporting
Deliver fast, governed reporting through Looker and Looker Studio, connected to BigQuery and designed to perform reliably under real business demand.
Managed operations
Provide 24/7 monitoring, query and storage optimisation, performance tuning and incident response across your Google Cloud data and AI estate.
EXPLORE OUR SERVICES
Choose the service that fits your goals
From managed operations to AI, our services help you get more value from Google Cloud across data, reporting, automation and AI workloads.
GOOGLE CLOUD MIGRATION PATHS
Move to Google Cloud from your current platform
A Google Cloud migration does not need to disrupt critical reporting or applications. We assess dependencies, select the right Google Cloud services and move priority workloads in controlled phases.
Legacy data warehouse to BigQuery
Move beyond ageing appliances, capacity limits and fixed infrastructure to BigQuery, gaining serverless scale, stronger reporting performance and a more flexible foundation for growing analytics workloads.
Redshift / Synapse / Teradata to BigQuery
Move analytics workloads onto BigQuery’s serverless architecture, removing clusters to size and manage while creating a scalable, lower-maintenance foundation for reporting, analysis and growing data volumes.
Oracle / PostgreSQL to AlloyDB
Move relational workloads to AlloyDB while maintaining PostgreSQL compatibility, gaining managed performance, high availability and cloud-scale operation through a controlled migration approach designed to minimise disruption.
HBase / NoSQL to Bigtable
Move high-throughput NoSQL workloads to Bigtable, reducing infrastructure overhead while gaining managed scale, resilience and reliable performance for applications handling large volumes of operational and time-series data.
FEATURED SUCCESS STORY
Trust your data availability with expert operational monitoring and support
Trust your data availability with expert operational monitoring and support
Read the AWS success story →
80%
reduction in manual data entry
3X
faster document processing
HOW WE WORK WITH YOU
A clear path to value
We follow a proven three-stage approach to help you get the most from Google Cloud, with a focus on measurable outcomes.
01
Assess and design
Review your architecture, workloads and priorities, then define the right Google Cloud design, governance model and phased migration plan around business value and risk.
02
Build and migrate
Build pipelines, configure governance and move priority workloads through controlled cutovers that protect critical reporting, applications and business operations.
03
Optimise and run
Tune query performance, control costs and establish ongoing monitoring and support to keep the environment reliable, efficient and ready to scale as demand grows.
GOOGLE CLOUD FAQS
Frequently asked questions