Couchbase Announces Capella for Real-Time Data Analytics
At AWS re:Invent, Couchbase has introduced the Capella columnar service, a revolutionary addition to its cloud data platform aimed at empowering organisations to construct modern, real-time adaptive applications. The Capella columnar service, revealed today, incorporates a columnar store and extensive data integration within Couchbase’s database-as-a-service (DBaaS). This integration facilitates real-time data analysis on the same platform utilised for operational application workloads. Traditional hurdles in the database industry surrounding the reconciliation of real-time analytics and operational applications have impeded true real-time data analytics. Couchbase acknowledges this longstanding problem and strives to overcome it through the Capella columnar service. Capella columnar emerges as a game-changer by seamlessly integrating operational and real-time analytic applications into a unified database platform. This convergence eliminates friction, enabling the delivery of superior customer experiences, particularly those involving artificial intelligence. These experiences, termed “adaptive applications,” offer contextualised hyper-personalization driven by real-time analytic calculations. A major innovation of the Capella columnar service is its ability to eliminate the write-back latency gap for operational applications. This entails writing back real-time analytic results immediately to the operational database and the associated applications it serves. Key Features of Capella Columnar A column-oriented, Log-Structured Merge (LSM) plus B-tree structured storage engine for expanded analytic performance and capacity. Enhanced MPP-based computation engine supporting real-time calculations regardless of data size. Real-time ingestion capabilities powered by Apache Kafka for seamless data capture and extraction. File-based reads, imports, and exports for data stored in AWS S3, supporting various formats. Conversational coding using Capella iQ for natural language interactions with ChatGPT for SQL++ development. Native support for Tableau and PowerBI for analytic development and visualisation. New data APIs to read and write analytic measures back to operational applications. Addressing a potential comparison, Couchbase emphasises that Capella Columnar offers specialised and optimised storage containers for both transactional operational data and analytic data, providing better performance and scalability compared to MongoDB Atlas. The announcement also delves into the concept of adaptive applications, which dynamically adjust behaviour and features based on user preferences, environmental conditions, and real-time data inputs. Couchbase’s Capella columnar service aims to support the development of adaptive applications with its unique capabilities. Capella Columnar promises to deliver tangible benefits to customers. Improved agility and performance with fast, schemaless ingestion within Capella-powered applications. Stream ingestion from enterprise data sources in real time, allowing for a variety of data analysis in a single statement. Increased ease of use for developers with a unified SQL++ query language across operational and analytic applications. Reduced complexity and cost by converging operational and real-time analytics in one data platform.
Capella columnar emerges as a game-changer by seamlessly integrating operational and real-time analytic applications into a unified database platform.
At AWS re:Invent, Couchbase has introduced the Capella columnar service, a revolutionary addition to its cloud data platform aimed at empowering organisations to construct modern, real-time adaptive applications.
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["ChatGPT", "artificial intelligence", "AWS", "AI", "MongoDB", "ML", "RAG", "Aim", "analytics", "Kafka"]
["AI", "artificial intelligence", "ML", "analytics", "ChatGPT", "Aim", "RAG", "AWS", "Kafka", "MongoDB"]
Mohit writes about AI in simple, explainable, and often funny words. He's especially passionate about chatting with those building AI for Bharat, with the occasional detour into AGI.