HomePulse Engages Utility Customers with Personalized Smart Energy AnalyticsMay 6, 2015
This post is one in a series of quick-hit interviews with companies using Apache Cassandra™ and/or DataStax Enterprise (DSE) for key parts of their business. For this interview, we talked with Maxime Lemaire who is CIO at HomePulse (previously Wattgo).
“We’ve been able to stop worrying about things like performance, security, and things like that. DSE has provided us with everything we need and it has given us great peace of mind.”
DataStax: Max, thanks for chatting with us today. What can you tell us about HomePulse?
Max: We are a smart grid software company and we help utilities develop smart customer engagement applications. We utilize sensors to collect a person’s energy utilization and then provide analysis via customer-facing dashboards on their usage.
We’ve been in business for about three years now and have around 2,000 customers.
DataStax: Does your solution run in the cloud?
Max: We run partly in the cloud and partly on premise. Right now we manage about 6TB of data between them.
DataStax: What caused you to seek out a NoSQL database like Apache Cassandra™ and DataStax Enterprise?
Max: We collect data on the average of every 1-5 seconds, so that’s a lot of data points coming in from each customer. We started with MySQL three years ago, but that was much too low. Then we turned to HBase, but that proved to be too slow for both reads and writes as well. We then turned to Apache Cassandra™, which was much better and showed itself to handle time series data very well.
We also use a variety of development languages and were happy to receive a full stable of certified drivers from DataStax, which is a big deal for us. We currently use the Node.js, C++, and Java drivers along with the Apache Spark™ connector.
DataStax: So Apache Cassandra™ proved to be the only database that was able to collect all the incoming energy information in a performant way. Do your customers interact with the database in the dashboards?
Max: Yes, information from the Apache Cassandra™ database is used to power our web-based dashboards that customers interact with. All information is shown in real-time along with historical information and alerts.
DataStax: What caused you to use DataStax Enterprise (DSE) over open source Apache Cassandra™?
Max: DSE makes our life easier in a number of ways. First, it helps automate performance monitoring, tuning, and backup tasks. We use OpsCenter to manage a lot of these things.
Next, we use Apache Spark™ for our analytics and have a separate Apache Spark™ cluster running. In addition to that we had another, distinct Elasticsearch cluster running for search tasks. With DSE, we get Apache Spark™ built-in to a database cluster as well as search capabilities via DSE Search, which removes the need to have separate clusters of Apache Spark™ and Elasticsearch. We’re using DSE Search today and will be migrating our separate Apache Spark™ cluster to DSE soon.
DataStax: What advice would you give to someone just starting off with NoSQL?
Max: The key is understanding how data modeling works in Apache Cassandra™. This is the first thing to tackle. I would also recommend using a solution like DSE over open source Apache Cassandra™ because then you can focus on things like data modeling and not have to worry about managing and maintaining your clusters.
DataStax: How would you sum up the benefits you’ve realized with DSE?
Max: We’ve been able to stop worrying about things like performance, security, and things like that. DSE has provided us with everything we need and it has given us great peace of mind.
DataStax: Thanks for the time Max.
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