Big Data Computing
Process massive datasets, run complex analytics, and power real-time insights with cloud infrastructure built for Big Data.
Quick
start
Easy
to manage
GDPR
compliance
Tech support specialists are available 24 hours a day by phone or via the control panel.
We guarantee uninterrupted infrastructure work and its 99.9% availability covered in the Service Level Agreement (SLA).
VPS/VDS servers are powered by Intel Xeon Gold 6154. 3.1 GHz super-performance processors and solid-state drives.
Deploy the cloud for Big Data
Take advantage of Serverspace's cloud services to launch your
project in the cloud.
Create a virtual server for Big Data analysis in just 40 seconds. Deployment time is one of the best in the industry.
Perceive costs with the useful Serverspace pricing system and service billing in 10-minute increments.
Change the number of CPUs, the amount of RAM, disk space, and bandwidth in the control panel according to your needs.
Get high virtual server performance powered by 3.1 GHz Intel Xeon Gold processors and solid-state drives.
Collect data and drive your business forward
With cloud infrastructure and scalable storage, you’ll have complete control over big data and will be able to run workloads easily and safely.
Run a project with Serverspace infrastructure
Deploy a vStack or VMware-based server and get access to your cloud in 40 seconds.
Store files and unstructured data in S3-compliant storage and pay only for the storage you use.
Protect your data on an isolated network to create secure and reliable products for your users.
Configure NAT and firewall rules to protect your project data on isolated networks.
Predictable pricing
No limitations - just the best pricing plan for Big Data Computing.
FAQ:
What types of workloads require Big Data computing?
• Real-time analytics (e.g., fraud detection, recommendation engines)
• Machine learning and AI training
• Customer behavior analysis and personalization
• Financial modeling and risk analysis
• Genomics, scientific simulations, and research
• Social media and sentiment analysis
• Log processing and infrastructure monitoring
How is cloud computing used for Big Data analysis?
Cloud computing supports Big Data analysis by offering scalable, flexible and cost-efficient infrastructure. You can easily scale compute and storage as needed, process data using tools like Hadoop or Spark and store large datasets in cloud-based storage or data lakes.
It also enables integration with various data sources and provides access to managed analytics and machine learning tools - all without the need for upfront hardware investments.
Is Big Data computing secure and compliant with data regulations?
Yes, Big Data computing can be secure and compliant - especially on a trusted platform.
At Serverspace, we provide encryption at rest and in transit, isolated environments for each deployment, and role-based access controls. Our Tier III data centers ensure strong physical and network security and our infrastructure supports compliance with GDPR, LGPD, and other major data protection standards.
What infrastructure is needed to process Big Data?
• Distributed computing systems like Hadoop or Apache Spark for parallel data processing
• High-performance storage (e.g., SSDs, object storage, or distributed file systems)
• Scalable compute resources such as cloud-based VMs, GPU clusters, or HPC nodes
• Reliable networking with high bandwidth and low latency
• Data integration tools to collect and move data from various sources
• Monitoring and orchestration tools for managing workloads and ensuring system health
Need support?
If you need advice from a technician, log in to the control panel and create a support ticket.
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