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In 2016 our team of industry veterans began building a hyperscale data warehouse to tackle large, complex workloads.

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Published July 18, 2024

How Ocient Outperforms Druid in Real-Time Analysis of Large Compute-Intensive Workloads

Ocient was faster across the board, but the Ocient advantage grew larger as the compute load increased.

Technical Director of Professional Services Todd O'BrienBy Todd O’Brien, Director of Product Research

Performance, efficiency, and cost are the three critical factors that determine the success of a real-time analytics platform in any enterprise use case. It’s this trifecta of measurements that, as the Director of Product Research at Ocient, I’m always monitoring to deliver the best solutions for our growing customer base.

As we continue to expand our capabilities in industries such as AdTech and telecommunications, our team recently took a closer look at how Ocient performed when compared to another prominent player in real-time analytics — Druid — through running a comprehensive benchmark.

Today, I’m excited to share some of those results and the key takeaways from our research. While you can download the entire overview here, in this blog post we’ll explore the benchmark at a high level and help you understand how and where Ocient excels in delivering superior value in cost and implementation.

Ocient vs. Druid Benchmark Findings at a Glance

  • Ocient outperformed Druid across four categories — power/performance, concurrency, loading, and concurrency + loading. For the most compute-intensive workloads, Ocient’s performance was nearly double that of Druid.
  • When comparing on-premises implementations, Ocient’s list price is up to 69% lower than Druid’s. Ocient delivers further savings by consolidating systems, using industry-standard commodity hardware, and improving data center efficiency.
  • Ocient also offers more storage for less: When comparing list prices, an OcientCloud® solution provides nearly 9x more storage (945TB NVMe) for 64% less than an Imply Polaris solution with just 105.6TB S3 storage.
  • Ocient uses roughly 1/3rd as much disk space as Druid for the same dataset.

Compute Adjacent Storage Architecture® Built for Scale

When it comes to the most compute-intensive workloads, Ocient shines brightly against Druid. As the benchmark tests demonstrated that Ocient’s performance was nearly double that of Druid, the more compute-intensive the workload, the stronger Ocient’s Compute Adjacent Storage Architecture performed. Ocient is designed to manage high levels of concurrency, ensuring that even during peak load times, the platform maintains its performance standards.

A diagram showing Ocient’s Compute Adjacent Storage Architecture.

Where in other platforms, loading large datasets is often a bottleneck that can slow down operations, Ocient tackles this challenge head on. The platform’s dedicated data loading capabilities ensure that large amounts of data can be ingested efficiently, allowing for immediate analysis.

What sets Ocient apart is its ability to handle concurrent workloads while loading data. This capability ensures that ongoing analytical queries do not get interrupted or slowed down by data ingestion processes.

Cost-Effectiveness in the Cloud and On-Premises

Cost is often the most crucial factor when selecting an analytics platform. Ocient’s list price for private cloud and on-premises implementations is up to 69% lower than that of Druid. This significant cost advantage makes Ocient an attractive option for businesses looking to optimize their budgets without sacrificing performance.

Ocient delivers further savings by consolidating systems, which reduces the need for multiple specialized hardware setups. The platform utilizes industry-standard commodity hardware, which is both cost-effective and easy to replace or upgrade. Additionally, Ocient’s efficient use of data center resources translates to lower operational costs and improved overall efficiency.

When comparing list prices, an OcientCloud solution provides nearly nine times more storage (945TB NVMe) for 64% less than an Imply Polaris solution, which offers only 105.6TB S3 storage. This massive storage capacity allows enterprises to manage and analyze larger datasets without incurring prohibitive costs.

If you’d like to learn more about Ocient’s full deployment capabilities watch the video below with Senior Product Manager TJ Loughlin at our whiteboard.

1/3rd as Much Disk Space as Druid

Druid requires significantly more disk space to store the same dataset, which leads to higher storage costs and infrastructure requirements. Ocient’s approach provides both data resilience and storage efficiency, ensuring that data is both secure and available, even in the event of hardware failures.

Druid, while offering robust features for real-time data ingestion and querying, may require additional hardware resources when compared to Ocient.

More than an RTA Platform

For years, Druid has been a go-to solution for real-time analytics (RTA), making it easy to ingest and analyze data on the fly. But if you’re looking for something that takes it to the next level, check out the Ocient Hyperscale Data Warehouse™. Not only does it handle real-time data ingestion and analysis like Druid, but it also packs a punch with built-in data loading and transformation, machine learning capabilities, full SQL support, and high-resolution geospatial analytics.

As the modern data stack evolves, the key to finding the right solution is understanding the problem and the specific needs of the end user. As our benchmark shows, with nearly double the performance in compute-intensive workloads, high concurrency capabilities, efficient data loading, and significant cost savings, Ocient stands out as the ideal platform for data analysts and engineering teams looking to analyze the largest, most complex datasets in a streamlined platform.

If you’re ready to take your data analytics to the next level, download the entire benchmark or get in touch today to experience unparalleled performance, efficiency, and cost savings in your real-time analytics operations.