Real-time analytics

Does batch analytics no longer offer a competitive edge?

Create a real-time analytics solution that enables you to gain insights from data immediately after its collection.

Key challenges in building real-time analytics solutions

  • Large amounts of data: Processing and transferring terabytes of data for real-time analytics come at a high cost.

  • Real-time data processing and analysis: Achieving sub-second response times for data processing and analysis, handling high data throughput rates of millions of events per second.

  • Data integration: Seamlessly integrating data from diverse sources, such as databases, streaming platforms, and APIs.

  • Latency management: Minimizing processing latency to milliseconds or microseconds, achieving near-instantaneous insights and rapid response times.

  • Anomaly detection and forecasting: Utilizing advanced algorithms to detect anomalies in real-time and providing accurate forecasting models with low error rates based on historical and real-time data.

  • Data security and confidentiality: Implementing robust security measures, including end-to-end data encryption, access controls, and compliance with industry standards.

Real-time analytics use cases

Personalized marketing and customer engagement

Real-time analytics analyzes customer behavior in real-time, optimizing marketing strategies for enhanced engagement.

Fraud detection

Real-time analytics helps identify and prevent fraud by continuously analyzing data for anomalies in real time, mitigating risks promptly.

Predictive maintenance

Real-time analytics analyzes sensor data to detect equipment issues early, enabling proactive maintenance and minimizing costly downtime.

Real-time reporting, alerting and monitoring

Real-time analytics provides instant visibility into KPIs, aiding prompt decision-making and proactive problem-solving.

Supply chain optimization

Real-time analytics monitors inventory, demand, and logistics data, facilitating informed decisions and cost reduction.

IoT analytics

Real-time analytics analyzes streaming IoT data from sensors, cameras, etc., enabling automation, optimization, and actionable insights.

Why choose DoubleCloud?

With our platform you are free to either build a cost-efficient solution from scratch or enhance your existing batch analytics architecture by adding a data store that will significantly accelerate your analytics, achieving sub-second performance.

Enjoy benefits of our platform

Open-source and cloud agnostic

Use the original ClickHouse and Kafka distributives wherever you like without vendor lock-in.


Add more Kafka brokers or ClickHouse nodes and scale ingestion as you grow. For instance, the biggest production Clickhouse cluster is 2000 servers without performance degradation.

High availability and fault tolerance

Resizing and configuration without downtime, high availability configurations without a single point of failure for both: Clickhouse and Apache Kafka.

Hybrid storage

Hybrid storage on DoubleCloud platform allows to decrease the costs up to 3-4 times when working with large volumes of data.

Complianсe and security

DoubleCloud is SOC2, ISO/IEC 27001 certified provider and our solution ensures their most efficient backup, deployment, and scaling.

Customer use cases

Yango Tech launches real-time partner analytics with minimal time-to-market


  • Launching all their partner-facing analytics MVP only took a week

  • Partner reports are now updated in real time, not just once a day, as it used to be

  • Minimum entry threshold without specialized knowledge and expertise

Get started with DoubleCloud

  • Free, no-commitment trial
  • Up and running in 10 minutes