Data Processing
Infrastructure.

For consistent, long-running workloads, dedicated hardware costs 5-10x less than equivalent cloud compute. A cloud 4-core instance at $0.048/hr costs ~$35/month - for the same price at AlphaVPS, you get a High-Performance VPS with NVMe storage included. The savings increase with larger instances and longer runtime.

Yes. For single-node Spark processing, a VPS with 8+ cores and 16GB+ RAM handles significant workloads. For distributed Spark clusters, deploy multiple VPS instances or bare metal clusters and configure them as worker nodes. Full root access means you can install any framework - Spark, Hadoop, Flink, Dask, or Ray.

It depends on your workload. Multi-threaded processing (parallel ETL, Spark) benefits from EPYC CPUs with high core counts. Single-threaded tasks (Python scripts, some ML training) benefit from Ryzen's high clock speed. Our High-Performance VPS uses EPYC processors; our Ryzen VPS uses AMD Ryzen 7000 series.

For basic ETL and analytics: 4-8GB. For medium datasets with pandas/dplyr: 16-32GB. For large in-memory processing or ClickHouse: 64GB+. VPS plans offer up to 32GB RAM; dedicated servers offer 128GB-512GB+ for memory-intensive workloads.

Yes. Use cron for simple scheduling, Apache Airflow for complex DAG-based workflows, or systemd timers for service-based jobs. Since you have full root access, any Linux-compatible scheduling tool works. Your server runs 24/7, so scheduled jobs execute reliably without cold-start delays.

Yes, significantly. Data pipelines are often I/O bound - reading input data, writing intermediate results, and outputting final datasets. NVMe provides 5-10x the throughput and 50x lower latency compared to traditional HDDs. For ETL and analytics workloads, NVMe can be the difference between a 10-minute job and a 2-hour job.

Absolutely. Your VPS is fully isolated - no shared storage, no shared memory, no multi-tenant risk. Choose data center locations for compliance - our Germany and Bulgaria locations are ideal for GDPR-compliant data processing. Encrypt data at rest and in transit. Full root access means you control all security configurations.

Yes. Our GPU dedicated servers provide NVIDIA GPUs for ML training and inference. For CPU-based ML (scikit-learn, XGBoost, some PyTorch workloads), our standard VPS and dedicated servers provide excellent performance. See our AI & GPU solutions for GPU availability and custom configurations.