Optimizing Big Data Workloads to Reduce Costs

Continuous and Autonomous Big Data Optimization Solution Reducing Costs Through Improved Performance
Optimize big data workloads Optimize big data workloads

Reduce Processing Time and Increase Pipeline Throughput

Big Data workloads are growing fast and becoming more expensive. By using Granulate, applications run more efficiently, with fewer wasted resources, faster time to completion, accelerated pipeline throughput, resulting in reduced costs.
45%
Reduce
Compute Cost By
40%
Reduce
Processing Time By
47%
Reduce CPU Utilization By
0
Code Changes

Reduced Processing Costs, Optimized Performance

SUPPORTS ALL INFRASTRUCTURE

Whether your systems are on-prem, cloud-based or hybrid, Granulate supports all infrastructure, including EMR, Dataproc, HDInsight, Cloudera, MapReduce, Spark, PySpark, and more.
Granulate supports all big data infrastructure

REAL TIME CONTINUOUS ORCHESTRATION

Avoid constant monitoring and benchmarking with autonomous, continuous optimization, tuning big data workloads to their unique cost-performance sweet spot.
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Hit Your Big Data Workload Targets

optimized
Reduce processing costs across Spark, MapReduce, Kafka, Yarn, and more
real time continuous
Improve performance by continuously optimizing application runtime and resource allocation
scalable
Unburden your R&D team with continuous orchestration and zero code changes
improve agility
Meet your SLAs with faster job completion time

Complete More Jobs in Less Time

Granulate Allows Data Science, Data Engineering and Data Analysis Teams to Improve Performance With
YARN Resource Allocation

YARN RESOURCE ALLOCATION

Optimized to improve cluster density and remove overprovisioning waste.
Spark Dynamic Allocation

SPARK DYNAMIC ALLOCATION

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

CRYPTO & COMPRESSION ACCELERATION

Leveraging Crypto architecture, accelerators, and instruction sets for operations
Memory arenas optimization

MEMORY ARENAS OPTIMIZATION

Release of memory space and objects sizes to reduce allocation overhead
JVM Runtime Optimization

JVM RUNTIME OPTIMIZATION

JNI overhead reduction, execution control flow and reflection overhead optimization
rocket

3 Steps Through Just One init Script

1

Install

Start a free trial of Granulate on your Big Data applications
2

Evaluate

Let Granulate autonomously learn the data application and workloads
3

Deploy

Activate Granulate and immediately experience data performance improvements

See How It Works

ironSource Reduces Instances Count by 21% with Granulate

25
REDUCED CLOUD COSTS
21
REDUCED INSTANCES COUNT
29
INCREASE IN THROUGHPUT

ShareChat Reduces Kubernetes Costs by 20% with Granulate

25
RESPONSE TIME REDUCTION
20
REDUCTION IN COMPUTE COSTS
25
REDUCTION IN CPU UTILIZATION

Claroty Reduces EKS Spark Memory Usage by 50% with Granulate

50
REDUCTION IN MEMORY USAGE
20
REDUCTION IN COSTS
18
REDUCTION IN NODE COUNT

Securonix Cuts AWS Costs With Granulate

33
REDUCTION IN CAPACITY
45
CLUSTERS OPTIMIZED
100
EMR FLEET OPTIMIZED

Sharethrough Receives 156% ROI and 17% Cost Reduction with Granulate

26
REDUCTION IN CPU
UTILIZATION
17
REDUCTION IN EC2 COSTS
156
RETURN ON INVESTMENT
AWS
Java
Kubernetes

Zwift Improves Single Sign-On DataGrid Reducing Latency by 60%

60
Reduced Latency (P95)
14
Reduced Latency (P75)
25
Reduced CPU Utilization
Big Data
AWS
Kubernetes
Spark

Salt Security Cuts Spark Workload Costs by 40% with Granulate

40
Reduced Costs
15
Reduced Spark Time
35
Reduced CPU Utilization
Big Data
AWS
Kafka

Dream11 Improves Kafka Workload Performance and Reduces AWS Costs by 40%

40
Reduced Costs
40
Increased Throughput
50
Reduced CPU Utilization
Kubernetes
GCP

Kiwi.com Trims GKE Travel Tech Workload Core Count by Over 20%

20
Reduced CPU Utilization
1
Week for Results
AWS
Python

How MoEngage Achieved 40% Cost Reductions on AWS With Granulate

40
Reduced Costs
62
Reduced Latency
34
Reduced CPU Utilization
Big Data
AWS

How 605 Reduced EMR Costs by 60% in Less than a Week

60
Cost Reduction
30
CPU Utilization Reduction
60
Average Job Completion Time Reduction
GCP
Python

Nylas Achieves Over 35% Cost Reduction on GCP Leveraging Granulate

35
Cost Reduction
58
Latency Reduction
35
Throughput Increase
Python
Big Data

Mobileye Reduced 45% On Their AWS Costs Leveraging Granulate

45
Reduced AWS Costs
44.5
Faster Job Completion Time
Java
AWS

How SundaySky slashed AWS costs by 15% with no R&D efforts in only one week

15
Bidder Service Reduced Costs
20
Bidder CPU Utilization Reduction
Java
AWS

How Fyber slashed AWS costs by 20% with no code changes in only one week

20
Reduced Compute Costs
17
Reduced Response Time
15
Increased Throughput
Python
AWS
Big Data

How Granulate helps Singular reduce cost by 35% on mission-critical services on Amazon ECS

43
Average Job Completion Time Reduction
55
Attribution Service Reduced Average Latency
30
Data Pipeline Service Reduced Costs
Java
AWS

How Nativo achieved over 22% cost reduction in a week without any code changes or R&D efforts

31
Reduced Average Latency
18
Increased Throughput
10
Reduced CPU utilization
Java
AWS
Big Data

How AppsFlyer cut compute costs by 30% with no code changes

25
Spark cost reduction
35
Kafka cost reduction
30
Annual cost reduction
Kubernetes
Node.js
On-Premise

How PicsArt cut compute costs by 28% with zero R&D efforts

10
Reduced CPU Utilization
28
Reduced Compute Costs
12
Reduced Latency
Kubernetes
AWS
Java

How Perion cut compute costs by 52% with no R&D efforts

60
Reduced CPU Utilization
52
Reduced Compute Cost
10
Reduced Response Time
Kubernetes
AWS
Go

How Coralogix cut compute costs by 45% with no R&D efforts

29
Reduced CPU Utilization
45
Reduced Compute Cost
15
Increased Throughput
On-Premise
Java

How StartApp cut compute costs by 33% in just two weeks

25
Reduced CPU Utilization
33
Reduced Compute Cost
30
Reduced Latency
AWS
Python

Bigabid uses Granulate to dramatically reduce bid timeouts, latency, and compute costs

90
Fewer Bid Timeouts
60
Reduced Cloud cost
70
Reduced P95 Latency
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