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DataFunSummit
DataFunSummit
Apr 24, 2023 · Artificial Intelligence

OpenMLDB: A Production‑Grade Feature Platform for Consistent Online and Offline Machine Learning

OpenMLDB is an open‑source machine‑learning database that delivers a production‑grade, consistent online‑offline feature platform for real‑time AI applications such as recommendation, risk control and fraud detection, offering millisecond‑level feature computation, dual SQL engines, extensive ecosystem integration, and a roadmap of new capabilities.

AIFeature StoreOpenMLDB
0 likes · 13 min read
OpenMLDB: A Production‑Grade Feature Platform for Consistent Online and Offline Machine Learning
ITPUB
ITPUB
Dec 21, 2022 · Databases

How OpenMLDB Guarantees Real‑Time, Consistent Features for Machine Learning at Scale

This article explains the data and feature engineering challenges of deploying machine learning, introduces OpenMLDB’s open‑source architecture—including offline Spark‑based processing, a high‑availability online engine with dual‑layer memory indexes, snapshot/binlog persistence, and pre‑aggregation techniques—then showcases real‑world case studies and the project’s roadmap.

Feature StoreOpenMLDBReal-time analytics
0 likes · 15 min read
How OpenMLDB Guarantees Real‑Time, Consistent Features for Machine Learning at Scale
DataFunTalk
DataFunTalk
Dec 13, 2022 · Artificial Intelligence

End-to-End Machine Learning Application Using OpenMLDB and Alibaba Cloud MaxCompute

This article demonstrates how to build a complete end-to-end machine-learning workflow for taxi trip duration prediction by integrating OpenMLDB with Alibaba Cloud MaxCompute’s serverless services, covering environment setup, offline data ingestion, feature extraction, model training, deployment, and real-time online inference within 20 ms.

Feature StoreMaxComputeOpenMLDB
0 likes · 13 min read
End-to-End Machine Learning Application Using OpenMLDB and Alibaba Cloud MaxCompute
DataFunTalk
DataFunTalk
Sep 3, 2022 · Databases

OpenMLDB: An Open‑Source Machine Learning Database for Consistent Online and Offline Feature Serving

This article presents OpenMLDB, an open‑source machine learning database that unifies offline and online feature computation with millisecond‑level latency, outlines its development history, architecture, recent 0.6.0 enhancements, ecosystem integrations, and multiple real‑world deployment case studies across finance, banking, research, and marketing domains.

AIFeature StoreOpenMLDB
0 likes · 16 min read
OpenMLDB: An Open‑Source Machine Learning Database for Consistent Online and Offline Feature Serving
DataFunTalk
DataFunTalk
Aug 25, 2022 · Big Data

Applying OpenMLDB for Efficient AI Toolchain and Data‑Driven Architecture at Akulaku

This article presents Akulaku’s practical experience with OpenMLDB, describing the company’s data‑driven requirements, the design of a unified stream‑batch architecture, implementation details across offline, online and RocksDB modes, and future recommendations for high‑performance, scenario‑agnostic big‑data processing.

AIBatch ProcessingOpenMLDB
0 likes · 17 min read
Applying OpenMLDB for Efficient AI Toolchain and Data‑Driven Architecture at Akulaku
DataFunTalk
DataFunTalk
Aug 3, 2022 · Artificial Intelligence

Building a Complete Machine Learning Application with OpenMLDB and OneFlow: JD High‑Potential User Purchase Intent Prediction

This tutorial demonstrates how to use OpenMLDB together with OneFlow to build an end‑to‑end machine‑learning pipeline for predicting high‑potential JD users' purchase intent, covering environment setup, data loading, SQL table creation, offline feature extraction, DeepFM model training, model serving, online feature extraction, deployment, and real‑time inference.

DockerFeatureEngineeringModelServing
0 likes · 22 min read
Building a Complete Machine Learning Application with OpenMLDB and OneFlow: JD High‑Potential User Purchase Intent Prediction
DataFunTalk
DataFunTalk
May 31, 2022 · Artificial Intelligence

Using DolphinScheduler OpenMLDB Task for End‑to‑End MLOps Workflow

This article introduces the DolphinScheduler OpenMLDB Task, explains how it integrates OpenMLDB's feature platform into DolphinScheduler workflows to create a complete MLOps pipeline, and provides a step‑by‑step demonstration using the TalkingData ad‑fraud detection dataset from Kaggle.

DolphinSchedulerMLOpsOpenMLDB
0 likes · 7 min read
Using DolphinScheduler OpenMLDB Task for End‑to‑End MLOps Workflow
DataFunTalk
DataFunTalk
Apr 20, 2022 · Big Data

OpenMLDB Pulsar Connector: A Real‑time Data Integration Guide

This article presents a step‑by‑step tutorial on using the OpenMLDB Pulsar Connector to stream real‑time data from Apache Pulsar into OpenMLDB, covering connector architecture, key features, Docker‑based installation, sink configuration, schema registration, message production, verification queries, and future roadmap details.

Apache PulsarConnectorData Integration
0 likes · 13 min read
OpenMLDB Pulsar Connector: A Real‑time Data Integration Guide
DataFunTalk
DataFunTalk
Mar 8, 2022 · Databases

OpenMLDB 0.4.0 Full-Process Features and Quick‑Start Guide for Building End‑to‑End Online AI Applications

This article introduces the new full‑process features of OpenMLDB 0.4.0, explains its unified online/offline storage, high‑availability task management, and end‑to‑end AI workflow, and provides step‑by‑step instructions for quickly deploying both single‑node and cluster versions to run a complete online AI application.

AIWorkflowDistributedSystemsFeatureEngineering
0 likes · 24 min read
OpenMLDB 0.4.0 Full-Process Features and Quick‑Start Guide for Building End‑to‑End Online AI Applications
DataFunTalk
DataFunTalk
Jan 21, 2022 · Databases

Akulaku’s Adoption of OpenMLDB: Business Scenarios, Technical Architecture, and Evolution Recommendations

This article outlines Akulaku’s background, explores its business scenarios and challenges, details how OpenMLDB’s unified feature‑engineering platform and consistent technology stack address real‑time and offline data processing needs, presents performance comparisons across use cases, and offers cost‑benefit analysis and future improvement suggestions.

FinTechOpenMLDBfeature engineering
0 likes · 18 min read
Akulaku’s Adoption of OpenMLDB: Business Scenarios, Technical Architecture, and Evolution Recommendations