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
Develop an interactive, real time dashboard for a leading Supply Side Platform to allow their publishers to view ad performance reports
Process close to 1GB/sec data while ensuring no data loss
Create an interactive real-time dashboard which is both flexible and insightful
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
Build a realtime, scalable analytics system to calculate billing metrics while keeping processing costs below threshold.
Scale the system to process more than 10 terabytes log data per month
Ensure high accuracy in billing and low processing cost
Processing cost reduced by 90% without an accuracy trade-off using sophisticated statistical algorithms.
IOT – MACHINE DATA
Transform GBs of factory shop floor data streams in seconds
Transform GBs of data streams in seconds.
Meet SLA requirements while ensuring zero data loss and high accuracy
Our streaming platform consumes data from SFTP and SQS, perform transformations and write output to a database, meeting latency requirements.
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.
After a look at how Spark Streaming works, and discussing good production practices for Spark Streaming, this blog is about making your Spark streaming implementation fault tolerant and Highly available.
Pig, compared to a Hadoop MapReduce program, dramatically reduces the time required for the development and execution of data analysis tasks. Pig latin syntax is as simple as SQL. It is as extensible as mapreduce […]
Mesos High Availability Cluster:
Apache Mesos is a high availability cluster operating system as it has several masters, with one Leader. The other (standby) masters serve as backup in case the leader master fails. Zookeeper elects […]