6 posts tagged with "Customer Stories"
Customer success stories and case studies
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Zero Pipeline Failures, 50% Faster Loads: How Xeno Rebuilt Their Data Foundation on OLake
How Xeno replaced AWS DMS with OLake for MySQL CDC, cutting full-load time nearly 50% and ending schema-change pipeline failures, all self-hosted on Kubernetes.
Reliable Lakehouse Ingestion at Scale: How LendingKart Improved Data Correctness and Compressed Lake Ingestion Volume by 100×
How LendingKart reduced daily MongoDB data movement from gigabytes to megabytes while completing an 11 years historical backfill that their Debezium + Spark setup couldn't deliver reliably.
PhysicsWallah Evaluates MongoDB CDC Ingestion into a Lakehouse with Apache Iceberg and OLake
At PhysicsWallah, the Data Engineering team operates a large-scale lakehouse platform that powers analytics, reporting, and AI-driven use cases. A significant portion of operational data originates from MongoDB, making reliable and scalable CDC ingestion a foundational requirement.
From 40-Minute to Sub-Minute Segmentation Queries: How Bitespeed rebuilt its customer segmentation engine using OLake and Apache Iceberg
Bitespeed is a customer engagement and messaging platform built for modern commerce brands. Learn how they rebuilt their segmentation engine using OLake and Apache Iceberg without breaking their budget.
Astrotalk's Migration to Databricks: How OLake Replaced Google Datastream for Large-Scale Database Replication
Astrotalk runs one of India's largest astrology platforms, serving **millions** of users and handling large volumes of transactional data across PostgreSQL and MySQL. As the company began shifting from Google BigQuery to a Databricks-based lakehouse, they needed a reliable way to replicate databases to S3.
Cordial's Path to an AI-Ready Lakehouse: Large scale Multi-Cluster MongoDB Ingestion with OLake
Cordial, a leading marketing automation platform, is unifying thousands of MongoDB collections into a single Apache Iceberg based lakehouse architecture to power its next generation of AI agents.