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StarTree unveils new features for real-time analytics

Today

StarTree has announced a suite of new features aimed at addressing data management and security challenges as enterprises transition to real-time analytics.

Many organisations are shifting towards real-time analytics, facing the challenge of managing dynamic data at large scales. Real-time analytics differs from batch processing, as it requires solutions that ensure performance, security, and reliability in constantly changing environments. This complexity is seen in ventures like LinkedIn, which processes over 650,000 queries per second with Apache Pinot, Stripe's handling of approximately 1 PB of data, and Uber achieving a 99th percentile query latency of just 100 milliseconds.

The new features introduced by StarTree Cloud include "Pauseless Ingestion," designed to maintain data freshness on a large scale by ensuring continuous data flow during segment building and uploads. This ensures that businesses can provide real-time insights without disruption, crucial when organisations ingest tens of millions of messages per second.

StarTree has also launched a "Performance Manager" to facilitate the quick scaling of operations and reduce the time taken to derive value from Apache Pinot. This tool offers an intuitive, machine-learning-powered interface to assist teams in optimising query performance. It reviews query structures and metrics to suggest improvements, such as indexes and bloom filters, enhancing performance while demanding less manual effort.

An additional feature is "Schema Evolution," which allows real-time databases to adapt to new fields, indexes, or altered data types without operational disruption. This ensures that applications relying on evolving data flows remain consistent and functional.

"Data Backfill" enables users to reload past data to address any inaccuracies or omissions in data flows. This automation preserves data consistency, which is crucial for maintaining the integrity of real-time analytics by ensuring information remains accurate and up-to-date.

Furthermore, StarTree has introduced "Role-Based Access Control (RBAC) Management," enhancing security and simplifying user administration in real-time data environments. This feature allows organisations to manage user access efficiently based on roles, securing sensitive data even when accessed within sub-second windows.

Kishore Gopalakrishna, Co-founder and CEO of StarTree, stated, "StarTree's new features bridge a crucial gap in real-time analytics, enabling organisations to scale with the reliability and control typically seen in batch systems. By tackling critical challenges in data management and security, StarTree helps organisations better leverage real-time insights, enhancing their ability to scale operations efficiently."

Paul Nashawaty, Principal Analyst, AppDev, theCUBE Research, commented, "Real-time analytics presents a distinct challenge compared to batch-based analytics, as it requires instant adaptation to data changes while maintaining stringent performance demands. Industry research found that 75% of organisations struggle with the complexity and latency associated with traditional real-time analytics solutions."

Nashawaty continued, "StarTree is bringing essential improvements to real-time analytical databases, paving the way for broader adoption of real-time analytics across many industries. It enables businesses to gain real-time insights from their data and make faster, more informed decisions."

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