
Trino
Fast distributed SQL query engine for big data analytics.

Build Faster. Scale Smarter. With the World's Data Streaming Platform, by the original co-creators of Apache Kafka®

Confluent is a data streaming platform built upon Apache Kafka, designed to enable organizations to build real-time data pipelines and streaming applications. It provides a unified platform for data integration, processing, and governance. Key features include a serverless auto-scaling architecture, which eliminates the need for manual capacity management. Confluent simplifies building event-driven applications, processing data streams with fault-tolerant apps and microservices that respond to business events in real time. Use cases range from real-time inventory management and fraud detection to personalized customer experiences and AI-powered analytics. Confluent aims to replace costly point-to-point integrations with a centralized data streaming solution, ensuring data quality and enabling AI/ML applications with access to real-time data.
Confluent is a data streaming platform built upon Apache Kafka, designed to enable organizations to build real-time data pipelines and streaming applications.
Explore all tools that specialize in event processing. This domain focus ensures Confluent delivers optimized results for this specific requirement.
A streaming SQL engine that enables real-time data transformation and enrichment using SQL queries.
A central repository for managing and governing Kafka schemas, ensuring data consistency and compatibility across applications.
Extends Kafka storage to cheaper object stores (e.g., AWS S3) for long-term data retention and cost optimization.
Enables deploying Kafka clusters across multiple geographic regions for disaster recovery and low-latency access to data.
Securely share data streams between different teams, applications, and business units within the organization.
1. Sign up for a Confluent Cloud account or deploy Confluent Platform.
2. Configure Kafka Connect to ingest data from source systems (e.g., databases, APIs).
3. Define data streams and topics within Kafka to organize data.
4. Use ksqlDB or Kafka Streams to process and transform data in real-time.
5. Integrate with monitoring tools (e.g., Prometheus, Grafana) to observe data pipeline health.
6. Develop event-driven applications using Kafka client libraries (Java, Python, Go).
7. Implement data governance policies using Confluent Schema Registry and RBAC.
All Set
Ready to go
Verified feedback from other users.
"Generally positive sentiment towards Confluent's reliability and scalability, but some users note complexity in configuration and cost."
Post questions, share tips, and help other users.

Fast distributed SQL query engine for big data analytics.

Unlocking insights from unstructured data.

A visual data science platform combining visual analytics, data science, and data wrangling.

Open Source OCR Engine capable of recognizing over 100 languages.

Liberating data tables locked inside PDF files.

Move your data easily, securely, and efficiently with Stitch, now part of Qlik Talend Cloud.

Open Source High-Performance Data Warehouse delivering Sub-Second Analytics for End Users and Agents at Scale.