Real Time Streaming Platform

on

Apache Spark

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OUR CUSTOMERS

  • CAPILLARY

ARCHITECTURE

SigStream

PLATFORM

Platform Image

OUR CUSTOMERS

Capillary
FusionOps
PubNub

FEATURES

Fully Managed

Fully Managed

  • One click deployment
  • 24/7 SLA driven production support

High Performance

High Performance

  • Over million events per second
  • Scale to 100s of nodes

Deep Integration & Support

Deep Integration & Support

  • Multiple sources and Databases out of the box (Kafka, RabbitMQ, SQS, NoSQL DBs, Relational DBs, HDFS ….)
  • Cluster provisioning and management with autoscaling

Mission Critical Reliability

Mission Critical Reliability

  • 24/7 high availability
  • Completely Secure Setup
  • Zero data loss

SOLUTIONS

AD ANALYTICS

Problem

  • Develop an interactive, real time dashboard for a leading Supply Side Platform to allow their publishers to view ad performance reports

Challenges

  • Process close to 1GB/sec data while ensuring no data loss
  • Create an interactive real-time dashboard which is both flexible and insightful

Solution

  • Using SigStream, our Streaming Platform, we processed the incoming data at over a million events/sec and generated the required visualizations using SigView, our real-time dashboarding tool

LOG ANALYTICS

Problem

  • Build a realtime, scalable analytics system to calculate billing metrics while keeping processing costs below threshold.

Challenges

  • Scale the system to process more than 10 terabytes log data per month
  • Ensure high accuracy in billing and low processing cost

Solution

  • Processing cost reduced by 90% without an accuracy trade-off using sophisticated statistical algorithms.

IOT – MACHINE DATA

Problem

  • Transform GBs of factory shop floor data streams in seconds

Challenges

  • Transform GBs of data streams in seconds.
  • Meet SLA requirements while ensuring zero data loss and high accuracy

Solution

  • Our streaming platform consumes data from SFTP and SQS, perform transformations and write output to a database, meeting latency requirements.

TEAM SIGMOID

Sigmoid provides a completely managed, enterprise grade platform for Real Time Streaming Analytics on top of Apache Spark addressing varied use cases across industry verticals like Ad analytics, Fraud Detection, Sensor Data Analytics, Log Analytics, among others. The platform provides one-click automated cluster deployment, cluster health monitoring, job performance statistics, 24/7 high availability, security and zero data loss features and can process over a million events/sec

Mayur RustagiBig Data Developer
Mayur has 4 years experience in building end-to-end architecture for big data applications. His role is to create the vision and bring coherence to all the technology aspects at Sigmoid. He graduated from IIT Kharagpur with a Masters in Computer Science, and has created systems for digesting terabytes of data.
Rahul Kumar SinghData Scientist
Rahul specializes in solving diversified and complex business problems using a data driven approach. He is an expert in Predictive Modeling, Machine Learning, Data Mining, Text analysis, Natural Language Processing and Signal Processing. Rahul maintains a good rapport with clients and helps them to take informed business decisions by helping them in getting actionable insights from their data sources. He completed his Bachelors and Masters in Electrical Engineering from IIT Kharagpur.
Lokesh AnandBusiness Development
Lokesh has 4 years of experience across Technology & FMCG domain in project management & operations. He leads business development and operations at Sigmoid Analytics. He completed his bachelors and masters in Electrical Engineering from IIT Kharagpur.

OUR RECENT BLOGS

Cost Effective Data Processing at Scale using Spark

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