Autonomous Continuous Optimization for Big Data Workloads

  • Reduce processing costs on Spark, MapReduce, Kafka, and more
  • Improve performance by continuously optimizing application runtime and resource allocation
  • Unburden your R&D team with continuous orchestration and ZERO CODE CHANGES
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The next step in your big data journey starts here

Whether your systems are on-prem, cloud-based or hybrid Granulate supports all infrastructure:

Execution engines

kafkakafkasparkspark-apachetezpysparkpysparktezHadoopHadoop

Platform

cloud dataproccloud dataprocAWS EMRAWS EMRHDinsightHDinsightclouderaFramedatabricksdatabricks

RESOURCE
ORCHESTRATION

hadoop yarnhadoop yarnkuberneteskubernetesmesosmesos

Single, multi
& Hybrid cloud

awsawsAzure Logoagoogle cloudgoogle cloud

How Can You Achieve Reduced CPU Utilization and Improved Processing Time?

YARN

YARN Resource Allocation

Optimize the allocation of your YARN resources to improve cluster density and remove overprovisioning waste.

Spark

Spark Dynamic Allocation

Optimized dynamic allocation and removal of executors based on the job patterns and predictive idle heuristics.

security

Crypto & Compression Acceleration

Leverage Crypto architecture, accelerators, and instruction set for operations.

Memory

Memory Arenas Optimization

PGO allocation and release of memory space and objects sizes to reduce allocation overhead

java

JVM Runtime Optimization

JNI overhead reduction, execution control flow and reflection overhead optimization

Trusted By

mobileye mobileye (2)
salt salt
singular 2 singular 2
appsflyer appsflyer
605 605
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inMarket-1-1 inmarket
deezer deezer
securonix securonix
zeotap_colorlogo_RGB_medium zeotap_colorlogo_RGB_medium
nubank nubank

Hear from our customers

With better latency conditions and more efficient CPU utilization, we were able to get more out of our machines and cut Spark job completion time drastically [with Granulate].
Gal Porat
Gal Porat, DevOps Manager at Salt Security

Hear from our customers

Because our new code gets seamlessly accelerated every day, we can develop more quickly, and this means our time to market is much faster
Tal Babaioff
Tal Babaioff, VP Mapping and Localization

Hear from our customers

I did not expect to actually improve performance so much that we could scale down our workload 35% and still get an almost 60% improvement to latency
Caleb Geene
Caleb Geene, Director of Site Reliability Engineering

Hear from our customers

With better latency conditions and more efficient CPU utilization, we were able to get more out of our machines and cut Spark job completion time drastically [with Granulate].
Gal Porat
Gal Porat, DevOps Manager at Salt Security

Hear from our customers

Because our new code gets seamlessly accelerated every day, we can develop more quickly, and this means our time to market is much faster
Tal Babaioff
Tal Babaioff, VP Mapping and Localization

Hear from our customers

I did not expect to actually improve performance so much that we could scale down our workload 35% and still get an almost 60% improvement to latency
Caleb Geene
Caleb Geene, Director of Site Reliability Engineering

Optimize Big Data Processes with Granulate

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