Your Infrastructure Benchmarking Team
ServerPicks is a 7-person cloud infrastructure team based in Boston, Massachusetts. We benchmark, compare, and recommend cloud hosting providers for data-intensive workloads.
Our Story
ServerPicks started in a shared workspace in Somerville, MA. Our founding team of four infrastructure engineers kept running into the same problem: cloud hosting recommendations were built for web developers, not for people processing satellite imagery, running real-time GIS services, or ingesting LiDAR point clouds at scale.
We needed to know: which cloud provider delivers the fastest GDAL raster operations? Which VPS host handles PostGIS spatial joins without falling over? How does object storage performance vary across providers when you're serving geotiff tiles to millions of users?
Nobody had answers. So we built our own benchmark infrastructure — a test lab in Boston running standardized geospatial workloads against every major cloud provider. Today, we've grown to a team of seven, and we publish our benchmark data openly so the geospatial community can make informed infrastructure decisions.
What Makes Us Different
Geospatial Systems Focus
We specialize in infrastructure for GIS, remote sensing, spatial analytics, and location intelligence workloads — not just generic cloud hosting.
Rigorous Benchmarks
Every provider is tested with geospatial benchmark suites: GDAL/OGR processing, PostGIS query throughput, tile serving latency, and raster compute performance.
Independent Analysis
No sponsored rankings, no affiliate bias. Our recommendations are based on real performance data collected from our Boston-based test infrastructure.
Global Perspective
We test from multiple geographic vantage points to provide latency and throughput data relevant to distributed geospatial systems.
The Team
Marcus Chen
Lead Geospatial Engineer
GIS architecture, PostGIS tuning, raster pipeline design. Formerly at Planet Labs.
Aisha Patel
Cloud Infrastructure Lead
Multi-cloud benchmarking, network latency analysis, cost optimization. Ex-AWS infrastructure team.
James Mitchell
DevOps & Automation
CI/CD pipelines, infrastructure as code, automated benchmark harnesses. Kubernetes specialist.
Sarah Chen
Data Scientist & Analyst
Performance data analysis, statistical modeling, benchmark methodology. PhD in Geospatial Science.
Marcus Wei
Full-Stack Engineer
Frontend architecture, Next.js development, and benchmark visualization. Builds the user-facing comparison tools.
Alex Chen
Technical Writer & Analyst
Cloud infrastructure research, technical writing, and benchmark reporting. Author of in-depth provider comparisons.
Alex Rivera
Network Engineer
Global network latency testing, CDN performance analysis, and multi-region benchmark coordination.
Our Benchmark Methodology
Every provider we review is tested against a standardized geospatial benchmark suite running from our Boston-based test infrastructure:
- GDAL/OGR Performance — raster and vector processing throughput using real-world datasets (Sentinel-2 imagery, OpenStreetMap extracts)
- PostGIS Query Throughput — spatial join performance, index scan speeds, and concurrent query handling
- Tile Serving Latency — MBTiles, PMTiles, and S3-based tile serving response times from multiple geographic regions
- Object Storage Geo-Performance — S3-compatible storage read/write throughput for geospatial data formats
- Cost-per-Benchmark — dollar cost to complete standardized geospatial processing tasks
We update our benchmarks quarterly. Pricing and features change frequently, so we encourage verifying details directly with providers before making purchasing decisions. Links to official websites are provided on every provider page.
Have a suggestion?
We're always improving. If you know a provider we should benchmark or have feedback on our methodology, reach out to the team.