Latest news with #OnlineTransactionProcessing
Techday NZ
3 days ago
- Business
- Techday NZ
Databricks launches Lakebase Postgres database for AI era
Databricks has launched Lakebase, a fully managed Postgres database designed specifically for artificial intelligence (AI) applications, and made it available in Public Preview. Lakebase integrates an operational database layer into Databricks' Data Intelligence Platform, with the goal of enabling developers and enterprises to build data applications and AI agents more efficiently on a single multi-cloud environment. Purpose-built for AI workloads Operational databases, commonly known as Online Transaction Processing (OLTP) systems, are fundamental to application development across industries. The market for these databases is estimated at over USD $100 billion. However, many OLTP systems are based on architectures developed decades ago, which makes them challenging to manage, inflexible, and expensive. The current shift towards AI-driven applications has introduced new technical requirements, including the need for real-time data handling and scalable architecture that supports AI workloads at speed and scale. Lakebase, which leverages Neon technology, delivers operational data to the lakehouse architecture — combining low-cost data storage with computing resources that automatically scale to meet workload requirements. This design allows for the convergence of operational and analytical systems, reducing latency for AI processes and offering enterprises current data for real-time decision-making. "We've spent the past few years helping enterprises build AI apps and agents that can reason on their proprietary data with the Databricks Data Intelligence Platform," said Ali Ghodsi, Co-founder and CEO of Databricks. "Now, with Lakebase, we're creating a new category in the database market: a modern Postgres database, deeply integrated with the lakehouse and today's development stacks. As AI agents reshape how businesses operate, Fortune 500 companies are ready to replace outdated systems. With Lakebase, we're giving them a database built for the demands of the AI era." Key features Lakebase separates compute and storage, supporting independent scaling for diverse workloads. Its cloud-native architecture offers low latency (under 10 milliseconds), high concurrency (over 10,000 queries per second), and is designed for high-availability transactional operations. The service is built on Postgres, an open source database engine widely used by developers and supported by a rich ecosystem. For AI workloads, Lakebase launches in under a second and operates on a consumption-based payment model, so users only pay for the resources they use. Branching capabilities allow developers to create copy-on-write database clones, supporting safe testing and experimentation by both humans and AI agents. Lakebase automatically syncs data with lakehouse tables and provides an online feature store for machine learning model serving. It also integrates with other Databricks services, including Databricks Apps and Unity Catalog. The database is managed entirely by Databricks, with features such as encrypted data at rest, high availability, point-in-time recovery, and enterprise-grade compliance and security. Market adoption and customer perspectives According to the company, hundreds of enterprises participated in the Private Preview stage of Lakebase. Potential applications for the technology span sectors, from personalised product recommendations in retail to clinical trial workflow management in healthcare. Jelle Van Etten, Head of Global Data Platform at Heineken, commented: "At Heineken, our goal is to become the best-connected brewer. To do that, we needed a way to unify all of our datasets to accelerate the path from data to value. Databricks has long been our foundation for analytics, creating insights such as product recommendations and supply chain enhancements. Our analytical data platform is now evolving to be an operational AI data platform and needs to deliver those insights to applications at low latency." Anjan Kundavaram, Chief Product Officer at Fivetran, said: "Lakebase removes the operational burden of managing transactional databases. Our customers can focus on building applications instead of worrying about provisioning, tuning and scaling." David Menninger, Executive Director at ISG Software Research, said: "Our research shows that the data and insights from analytical processes are the most critical data to enterprises' success. In order to act on that information, they must be able to incorporate it into operational processes via their business applications. These two worlds are no longer separate. By offering a Postgres-compatible, lakehouse-integrated system designed specifically for AI-native and analytical workloads, Databricks is giving customers a unified, developer-friendly stack that reduces complexity and accelerates innovation. This combination will help enterprises maximise the value they derive across their entire data estate — from storage to AI-enabled application deployment." Integration and partner network Lakebase is launching with support from a network of partners, including technology vendors and system integrators such as Accenture, Deloitte, Cloudflare, Informatica, Qlik, and Redis, among others. These partnerships are designed to ease data integration, enhance business intelligence, and support governance for customers as they adopt Lakebase as part of their operational infrastructure. Lakebase is now available in Public Preview with further enhancements planned in the coming months. Customers can access the preview directly through their Databricks workspace.
Mid East Info
05-03-2025
- Business
- Mid East Info
Alibaba Cloud's PolarDB Breaks TPC-C Benchmark World Record with Innovative ‘Three-Layer Decoupling' Architecture
The cloud-native database showcases record-breaking performance and enhanced efficiency. March 2025 – Alibaba Cloud, the digital technology and intelligence backbone of Alibaba Group, has set a new world record with its cloud-native relational database PolarDB in the TPC-C benchmark. Developed by the Transaction Processing Performance Council (TPC), the TPC-C benchmark evaluates the performance of Online Transaction Processing (OLTP) systems. According to the TPC-C results, PolarDB achieved 2.055 billion transactions per minute (tpmC), 2.5 times higher than the previous record holder, while reducing the cost per transaction (price/tpmC) by almost 40% to CNY 0.8 (USD 0.11). Additionally, during an 8-hour stress test, PolarDB successfully processed 2.2 trillion data operations with 100% data accuracy, and maintained a tpmC fluctuation rate of just 0.16%, an order of magnitude lower than the TPC-C benchmark requirement of 2%. PolarDB's achievement of 2.055 billion tpmC in the TPC-C benchmark is 59 times the peak transaction volume recorded during the Tmall 11.11 Shopping Festival in 2020. Dr Feifei Li, President of Database Products Business at Alibaba Cloud Intelligence, said: 'This remarkable achievement is a testament to our team's relentless pursuit of innovation and excellence in database technology. PolarDB's performance in the TPC-C benchmark showcases its capability to handle the most demanding workloads while emphasizing our commitment to providing cost-effective and scalable solutions. With innovative architecture, managing cloud-native databases will be as simple as 'building blocks'. We will continue to support our customers to effectively manage and utilize data to thrive in the digital era.' The TPC-C benchmark is designed to assess a database's performance under extreme conditions. It challenges a database to maintain data accuracy under significant stress, guarantee data consistency during software and hardware failure, and ensure data availability, consistency, and integrity under stress conditions. TPC-C is recognized as one of the most authoritative OLTP benchmarks in the industry. PolarDB's record-breaking performance is driven by its innovative architecture. Its Limitless Architecture features a 'three-layer decoupling' design, which enhances efficiency by enabling the independent scaling of computing, memory, and storage for optimal elasticity. This exceptional performance is further boosted through software-hardware integration and advanced database kernel optimization technologies, including transaction processing improvement, index structure refinements, and I/O path enhancements. PolarDB is a cloud-native relational database that is designed for business-critical database applications that require fast performance, high concurrency, and automatic scaling. This solution has supported the digital journey of over 10,000 enterprise customers across various sectors worldwide, including TNG eWallet, the largest fintech platform in Malaysia; Television Broadcasts Limited (TVB), a major player in Chinese TV program production based in Hong Kong; enish, Inc., a mobile game development company in Japan; and DOKU, one of Indonesia's leading payment technology companies. Alibaba Cloud offers a broad range of self-developed, cloud-native database products, including the relational database PolarDB, data warehouse AnalyticDB, multimodal database Lindorm, and Data Management Service (DMS), among others. For the fifth year in a row, Alibaba Cloud has been named a Leader in Gartner® Magic Quadrant™ for Cloud Database Management Systems (DBMS). About Alibaba Cloud: Established in 2009, Alibaba Cloud ( is the digital technology and intelligence backbone of Alibaba Group. It offers a complete suite of cloud services to customers worldwide, including elastic computing, database, storage, network virtualization services, large-scale computing, security, big data analytics, machine learning and artificial intelligence (AI) services. Alibaba has been named the leading IaaS provider in Asia Pacific by revenue in U.S. dollars since 2018, according to Gartner. It has also maintained its position as one of the world's leading public cloud IaaS service providers since 2018, according to IDC.
