Irisidea helps organisations build real-world Big Data applications that integrate and analyze high velocity data sources.
We integrate Kafka to support any big data use cases.
Right from designing, building new systems to fine-tuning existing systems, Irisidea offers a complete range of Apache Kafka & Confluent Kafka application consulting & solutions.
We help teams design and build platforms that successfully and efficiently meet business and technical requirements.
With extensive development, deployments and optimization experience with Kafka, we ensure high quality implementation on-prem and various cloud platform such as AWS, Google Cloud and Azure
We abide with the best practices when it comes to performance and storage goals, cluster resilience across availability zones, disaster recovery, integration between cloud and on-prem clusters, security requirements etc.
Our Kafka experts work with your team to review your existing solution, and share best practices, identify areas for improvement, how to avoid errors, provide hardware requirements, and more.
Our Kafka experts work alongside your team to review your current Kafka solution assessing it for reliability, scalability, latency, throughput, monitoring, log management, hardware, preventative maintenance, and more.
Our consultants can assist you not only with your Kafka solution but also with other critical components of your data architecture, providing a uniquely comprehensive approach.
Have one of our Kafka experts review your production upgrade plans and help you understand the differences between versions while maintaining your SLAs.
We’ve assisted companies to architect and optimize their Kafka solution. Our Kafka experts can help you save time and resources to avoid errors, apply best practices, and deploy high-performance streaming platforms that scale.
Apache Druid is a real-time analytics database designed for fast slice-and-dice analytics (“OLAP” queries) on large data sets. Most often, Druid powers use cases where real-time ingestion, fast query performance, and high uptime are important.
Druid is commonly used as the database backend for GUIs of analytical applications, or for highly-concurrent APIs that need fast aggregations. Druid works best with event-oriented data.