“Alooma Live makes it possible for data scientists and engineers to gain unprecedented visibility into their streams, so they can correct problems and be confident the intelligence being derived from their data is accurate, reliable and actionable,” Yoni Broyde, Co-founder and CEO of Alooma, says in a press release.ĭatawatch’s Panopticon software provides a real-time window atop a streaming OLAP databaseĪnother real-time visualization vendor to keep an eye on is Massachusetts-based Datawatch. The cloud-based software allows users to visualize individual data streams separately, which is useful when data flows differ for different sources. Recently the company announced Alooma Live, a new product that enables users to view data flows in real time. “Building something in house based on open source tools is going to be hard,” Weinberger says. While modern tools like Kafka, Storm, and Spark provide building blocks for experienced data engineers to work with, finding people with those skills is difficult, not to mention expensive. “When we see companies building something for real-time or the cloud, they’re not using the data integration tools of the past.” “Real-time data is becoming more and more important,” Alooma CTO Yair Weinberger told Datanami recently. The Israeli company has done the hard work of cobbling together open source software like Apache Kafka, Apache Storm, Redis, and Zookeeper into a shrink-wrapped product that gives users the capability to visualize and query streaming data.Īlooma Live lets users combine and visualize data in a Web-based GUI “Zoomdata is well-suited to business users and data scientists that need real-time insights from streaming data across a range of big data sources, or for developers that need to embed these insights in applications,” wrote Gartner analysts, who lauded the company’s native streaming capability as its number one strength.Īlooma is another company making waves in the big data lake. This sort of feature is likely what attracted investments by In-Q-Tel (the venture capital arm of the CIA) and attention from Gartner in the latest Magic Quadrant for Business Intelligence and Analytics Platforms, where Zoomdata debuted this month in the “Visionaries” quadrant. This, combined with the “data sharpening” feature of the software and the “Data DVR” capability to pause, rewind, and fast-forward the state of data flows, provides a very compelling experience for users who need to pull insights from the freshest data possible. ZoomData uses a “data sharpening” technique to help process billions of rows of data in real timeīut the Reston, Virginia company can also hook into Spark Streaming and bubble up visualizations of “micro-batch” data as they flow through Spark. Its use of “push-down” processing helps ensure better use of distributed computing resources. For example, the Zoomdata Server (which is largely based on Spark) can pull data from Hadoop, NoSQL stores, cloud apps, and traditional data warehouses, and make it available in the visual data discovery and query interface. Visual analysis of streaming data isn’t the only thing that Zoomdata does. That’s where products from vendors like Zoomdata, Alooma, Datawatch, and Splunk are aiming to make a difference. But these product lack intuitive user interfaces. Stream processing engines like Apache Spark, Apache Storm, Apache Samza, Apache Kafka, and Amazon Kinesis were built to provide the distributed platform upon which streaming applications can be built. That’s creating fertile ground for new class of visualization tools that promise to help analysts take action on emerging data streams. From clickstreams and transaction logs to mobile apps and the IoT, big data threatens to overwhelm customers relying on traditional BI tools to analyze it. Every day, the data deluge continues to grow.
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