Enelyzer’s Journey to Real-Time Sustainability Insights Using InfluxDB

By Jessica Wachtel / Developer
Dec 12, 2024

Enprove is a leading energy consultancy that helps energy-intensive industries transition to greener solutions. Through audits, expert advice, and their innovative SaaS platform, Enelyzer, Enprove drives sustainable change. More than just a platform, Enelyzer embodies visionary thinking, deep energy expertise, and a passionate commitment to a better future.

The challenge

Enelyzer is a SaaS platform that helps customers reduce their environmental footprint by adopting sustainable practices. It provides real-time or near real-time insights, reports, and visualizations, empowering businesses to refine their energy management strategies. Enelyzer’s interactive approach—asking targeted questions and delivering data-driven insights—includes essential insights on carbon footprint tracking and CGI reporting.

To deliver real-time insights, Enelyzer’s infrastructure needed robust querying and analytical capabilities. As Enelyzer scaled alongside new customers and workloads, performance bottlenecks emerged, first in its initial monolithic system built on Postgres and then in its newly modernized distributed architecture, where challenges persisted. With its focus on high cardinality time series data, Enelyzer required specialized infrastructure. Relational databases couldn’t meet these demands despite careful design and quality technology. After evaluating several options, Enelyzer’s engineering team added InfluxDB to the architecture, ensuring optimized performance for its unique time series requirements.

The solution

The Enelyzer engineering team modernized Enelyzer’s technology stack by adding a leading time series database, InfluxDB Cloud Dedicated. Cloud Dedicated is a single-tenant, managed, cloud-based time series database built for enterprise-grade workloads. The team also rewrote Enelyzer’s backend in Rust and added Telegraf for data collection. After incorporating InfluxDB and Telegraf, Enelyzer engineers found the performance boost they sought and could again deliver real-time querying and analytics to their customers.

Despite many changes, Enelyzer engineers attributed much of the performance gains to InfluxDB Cloud Dedicated. InfluxDB Cloud Dedicated offers custom partitioning, which optimizes queries and data storage. Enelyzer’s instance of InfluxDB Cloud Dedicated organizes data by measurement (similar to a database table) and point (individual data entry including timestamp, fields, and tags) using a custom petitioning strategy. This strategy enhances read and write performance by reducing concurrency and minimizing resource transactions.

Architecture

InfluxDB is compatible with all technical products and services within the open data ecosystem. This highly compatible nature allows the Enelyzer engineering team to deliver features faster and troubleshoot bugs quicker.

Enelyzer offers two customer-facing options for data visualization, charting, and analytics. Enelyzer’s UI provides intuitive charts, visualizations, and custom reports. For customers needing more advanced analysis and alerting, Enelyzer integrates directly with Grafana.

Data enters Enelyzer’s ecosystem through the open-source plugin agent Telegraf. Using Telegraf, Enelyzer continuously ingests data from diverse sources—such as MQTT, API, FTP, PLCs, and third-party or proprietary hardware—in real-time, avoiding vendor lock-in. Telegraf’s plugins for data collection, output, and transformations enable Enelyzer to maintain a unified data pipeline regardless of input and output sources.

In its latest modernization, Enelyzer’s engineering team added Mage AI to the stack. Mage AI manages task scheduling and ETL pipelines with InfluxDB, transforming incoming data as part of Enelyzer’s data normalization process. They also introduced ontologies with reasoning capabilities to support machine learning models.

By integrating InfluxDB Cloud Dedicated, Enelyzer engineers unlocked substantial performance gains directly supporting its mission to help businesses reduce their environmental footprint. Customers benefit from customized real-time reports and queries, AI-driven forecasting, and seamless real-time data collection from any data source. To learn more about Enelyzer, read the full case study here.