MENLO PARK, CA – Unravel Data, the only application performance management (APM) platform for simplifying big data operations, has announced that it has been included in Gartner’s March 2017 Market Guide for Hadoop Operations Providers. The report states, “Scaling Hadoop from small, pilot projects to large-scale production clusters involves a steep learning curve in terms of operational know-how that many enterprises are unprepared for.”
“Big Data offers extraordinary insights for organizations of all types, but running big data applications efficiently in production systems is still very complex,” said Kunal Agarwal, CEO of Unravel.
Key findings from the report outline the drivers of this complexity, including:
Unravel was built to simplify Big Data operations. More specifically, to enable moving apps from pilot to production at any scale with a small operations team; to deploy apps in a hybrid cloud while minimizing costs; and to run apps reliably across a diverse set of engines and platforms with guaranteed SLAs.
Unravel recently introduced its version 4.0 in March (available now), which included a new set of features for improving Big Data operations, such as:
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Unravel 4.0 is available now. Companies such as Autodesk and YP.com are using Unravel Data to manage and optimize their production Big Data systems. Unravel Data is available immediately for on-premises, cloud or hybrid Big Data deployments. Unravel Data currently supports Hadoop, Spark and Kafka, with plans to add support for other systems such as for data ingestion (Storm, Flume), NoSQL systems (Cassandra, HBase) and MPP systems (Impala, Drill). Unravel Data fully supports secure deployments with Kerberos, Apache Sentry, Encryption, etc.
Data sheet: https://unraveldata.com/wp-content/uploads/2019/01/unravel-data-sheet.pdf
Case studies: https://resources.unraveldata.com/