How Explorium Serves Enriched Data in Production 3-50x Faster with Firebolt
公司规模
Mid-size Company
地区
- America
国家
- United States
产品
- Firebolt
- Databricks Delta Lake
- Amazon Athena
技术栈
- SQL
- Apache Spark
- AWS
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
- Customer Satisfaction
技术
- 分析与建模 - 预测分析
- 平台即服务 (PaaS) - 数据管理平台
适用行业
- Software
适用功能
- 商业运营
服务
- 云规划/设计/实施服务
- 系统集成
关于客户
Explorium is a company that provides an external data acquisition and management platform. Their platform enables companies to make better business decisions by automatically discovering, connecting, and matching their own data with hundreds of curated data sources and thousands of external data signals. As Explorium grew, they faced challenges in managing and processing large volumes of data efficiently. Their customers rely on Explorium to provide enriched data quickly and accurately, which is critical for making informed business decisions. The company needed a solution that could handle increasing data volumes and provide consistent, fast performance to meet customer expectations.
挑战
Explorium faced significant performance challenges as their data and customer requests grew. Their existing setup, which involved using a Presto cluster on AWS for processing time series data, was unable to handle high loads efficiently. The shared nature of the Presto cluster meant that large jobs could impact the performance of other requests, leading to slowdowns and customer dissatisfaction. Explorium's data volumes and requests were expected to triple, necessitating a new solution to handle customer requests for time series data enrichment.
解决方案
Explorium evaluated several options, including other Presto solutions and Amazon Redshift, but found them lacking in terms of workload isolation and performance. They ultimately chose Firebolt for its ability to handle large data sets with decoupled storage and compute architecture. The implementation process took two months, with most of the work done using SQL. Explorium used Apache Spark to process raw data and loaded it into Delta Lake, then into Firebolt using an ELT process. Firebolt's primary indexes improved the performance of live queries, while larger offline requests were handled using federated queries. Explorium deployed a lower-cost three-node engine, relying on primary indexes for fast performance.
运营影响
数量效益
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