Sold by: Dual Bird Technologies INC
Deployed on AWS
DualBird provides hardware-level acceleration that supercharges Apache Spark and Amazon EMR on AWS, delivering 10x to 30x faster data processing, 50% to 90% lower cost, and eliminating manual performance tuning, with no changes required. By accelerating expensive operations (sorts, joins, aggregations, shuffles, Parquet encoding/decoding, etc) using purpose-built hardware on FPGA, DualBird breaks past the limits of CPU-based Spark.
DualBird operates under your existing data pipelines on AWS (EMR, Spark on EKS, etc), packaged as a simple Spark plug-in. Using DualBird requires no migration, code changes, or any other changes to your data stack.
Overview
DualBird provides hardware-level acceleration that supercharges Apache Spark and Amazon EMR on AWS. By accelerating expensive operations (sorts, joins, aggregations, shuffles, Parquet encoding/decoding, etc) using purpose-built hardware on FPGA, DualBird breaks past the limits of CPU-based Spark and delivers order-of-magnitude performance gains and dramatic cost reductions. The result is 10x to 30x faster data processing and 50% to 90% lower cost, elimination of manual performance tuning, and all with no changes required. Featuring:
- Game-changing speed: Overcome the performance limitations of the classic task-per-core architecture of CPU-based Spark.
- Always optimized: The majority of common Spark performance configurations simply do not exist when using our solution, providing best out-of-the-box performance and freeing you from constant tuning and calibration.
- Scale up effortlessly: Handle growing data demands without having to update your tech stack.
- Eliminate disk spills and data skew issues: Plan ahead better, avoid surprises.
- Reduce shuffle data: 3-5x less shuffle data, stored on local NVME devices. No EBS costs.
- Consistent and predictable pipeline cost and run time: Our system is invariant to data properties the CPU-based systems are sensitive to (e.g. high cardinality, high number of columns, etc), making it robust to changes and far more predictable.
How it works: DualBird natively accelerates existing Apache Spark workload on AWS, either on Amazon EMR or when deployed on EKS. The acceleration is packaged as a simple Spark plug-in, so there is no migration, no code changes, or any other changes to your data stack. Just change the cluster's EC2 instance type to ours, add our plugin to your job, and you are all set.
Highlights
- 10x to 30x faster data processing: Orders of magnitude higher performance ceiling, while preserving good cost even when using large clusters.
- 50% to 90% lower cost: Dramatically cuts EC2 cost and zeros-out EBS cost.
- Eliminates manual performance tuning: Optimized out-of-the-box with no tuning and calibration per job. Shortens dev cycles and eliminates constant maintenance. No changes required: Operates under your existing data pipelines on AWS (EMR, Spark on EKS, etc), packaged as a simple Spark plug-in. Using DualBird requires no migration and no code changes. Best out-of-the-box performance and effortless scale, without changing your data stack.
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Pricing
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
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Dimension | Cost/month | Overage cost |
|---|---|---|
DualBird Credits | $0.01 |
Dimensions summary
This listing uses a single pricing dimension: DualBird Credits. You buy under a contract and consume credits as you run the software. Pricing scales with the number of credits you commit to, rather than by separate tiers, instance sizes, or plan levels. There is one unit to track, which keeps billing straightforward. The software installs to accelerate Spark data processing on your own AWS infrastructure, and your credit commitment covers that usage.
Top-of-mind questions for buyers
Credits are the single billing unit you draw down under your contract. You consume them as you run the software to accelerate Spark data processing on your own AWS infrastructure. The more processing you run, the more credits you use. You track usage against your committed credit balance.
Credits are consumed as you run the accelerated software. When your clusters are not processing workloads, you are not drawing down credits for that idle time. Note that underlying AWS compute or storage charges are separate and continue based on AWS billing, independent of your DualBird credit consumption.
Your contract sets the number of credits you commit to upfront. If your processing needs grow beyond that balance, contact the vendor to discuss adding credits. The exact overage handling is not specified in the available information, so confirm the arrangement directly with Dual Bird Technologies.
www.dualbird.io
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