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Trusted Speedata Partner for Apache Spark and AI Data Acceleration
Geopits partners with Speedata, creator of the world's first Analytics Processing Unit (APU), to bring silicon-accelerated Apache Spark, ETL, and AI data pipeline performance to our managed data engineering services. The APU delivers up to 100x faster query performance and up to 90% lower total cost of ownership, with zero code changes required.
Geopits & Speedata Partnership
Geopits partners with Speedata, creator of the Analytics Processing Unit (APU) - the first processor purpose-built for Apache Spark SQL, batch ETL, and AI data preparation workloads. The partnership brings APU-accelerated performance to Geopits data engineering, DataOps, and analytics services, helping clients run Spark-based pipelines up to 100x faster at a fraction of the infrastructure cost.
What Geopits Supports with Speedata
We integrate Speedata's Analytics Processing Unit into Apache Spark environments to accelerate ETL, batch processing, and data pipeline workloads, with zero code changes required.
We tune and deploy Spark SQL workloads on APU hardware, delivering up to 100x faster query performance on complex joins, aggregations, and transformations.
We accelerate data preparation for AI and agentic AI workloads, from feature engineering through to model-ready datasets.
We help clients consolidate infrastructure and reduce total cost of ownership by up to 90% through APU-based acceleration.
We operate and monitor Spark-based data platforms running on APU-accelerated infrastructure, with proactive monitoring and performance reviews.
We assess and migrate existing Spark and big data analytics workloads onto Speedata APU infrastructure, covering planning, deployment, and validation.
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We configure access controls and security settings aligned to enterprise compliance requirements across APU-accelerated data environments.
Common Database Performance Challenges We Resolve
These are the performance issues Geopits encounters most frequently across enterprise database environments.
Silicon-Level Acceleration
Access to Speedata's Analytics Processing Unit (APU), the first processor purpose-built for Apache Spark SQL, batch ETL, and AI data preparation.
Up to 100x Faster Performance
APU-accelerated Spark workloads deliver dramatic query performance gains over general-purpose CPUs and GPUs.
Up to 90% Lower TCO
Infrastructure consolidation and reduced compute costs across ETL, analytics, and AI data pipelines.
Zero Code Change Integration
The APU integrates directly into existing Spark environments without requiring pipeline rewrites.
Deep Spark and Data Engineering Expertise
Geopits engineers bring existing data engineering and DataOps experience to APU-accelerated deployments.
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ISO Certified, Security First Operations
Data operations aligned to ISO 27001 and ISO 9001 certified processes.
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Frequently Asked Questions
What is Speedata's Analytics Processing Unit (APU)?
The APU is the world's first processor purpose-built for Apache Spark SQL, batch ETL, and AI data preparation workloads, executing these operations directly on silicon for up to 100x faster performance.
Do I need to change my code to use the Speedata APU?
No, the APU integrates with existing Apache Spark environments without requiring code changes.
How does Geopits use Speedata's APU in its services?
Geopits integrates APU-accelerated infrastructure into data engineering, ETL, and analytics services, helping clients run Spark-based pipelines faster and at lower cost.
What cost savings can I expect from APU-accelerated infrastructure?
Speedata's APU can reduce total cost of ownership by up to 90% through infrastructure consolidation and improved processing efficiency.
Can Speedata's APU accelerate AI and agentic AI workloads?
Yes, the APU accelerates data pipelines from ETL batch processing to data preparation for AI and agentic AI applications.
Is Geopits' Speedata-related work aligned to security and compliance standards?
Yes, data operations across APU-accelerated environments follow ISO 27001 and ISO 9001 certified processes.
Can Geopits help migrate our existing Spark workloads to APU-accelerated infrastructure?
Yes, Geopits assesses and migrates existing Spark and big data analytics workloads onto Speedata APU infrastructure, covering planning, deployment, and validation.
Ready to Transform Your Data?
Geopits works alongside your team as a strategic partner, starting with stabilizing your current databases, then modernizing your data infrastructure, and ultimately helping you unlock the full potential of AI.
Happy Clients so far
Databases Managed
Successful Migrations
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