Gartner’s ‘Market Guide for Hadoop Operations Providers’ Names Unravel as a Representative Vendor
MENLO PARK, Calif., April 18, 2017 — Unravel Data, the only application performance management (APM) platform for simplifying big data operations (DataOps), today 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:
- “The proliferation of processing engines and applications within Hadoop is further compounding operational complexity. It is also forcing data and analytics leaders to rethink their deployment choices and operational practices.”
- “Public cloud is becoming a popular deployment choice for Hadoop data lakes due to the evolution of turnkey services and provider-supported availability, the ability to scale compute and storage up and down rapidly and independently, and the flexibility to choose a wide variety of compute, storage and networking infrastructure.”
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:
- Intelligent APM for all types of big data applications – provides automated insights and in depth real-time visuals to detect, diagnose and resolve issues such as failed, slow, stuck applications. Supports ETL, analytical, SQL, machine learning and streaming applications.
- Automatic actions for ongoing operations issues – automatically detects and resolves issues such as missed SLAs, runaway applications, service degradations and bad configurations settings.
- Support for on-premises, cloud, and hybrid environments – Unravel works for all cloud, on-premise and hybrid environments. It also provides multi-cluster support allowing operations teams to analyze all performance data in one place.
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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. For more information and a free trial, please visit http://unraveldata.com/free-trial/.
About Unravel Data
Unravel Data is the Application Performance Management (APM) platform for big data applications. Unravel Data is the one APM tool big data operations (DataOps) teams will ever need to optimize, troubleshoot, and analyze performance. We didn’t just build another monitoring tool for big data, we re-invented APM to being full-stack, intelligent, and autonomous. Unravel Data guarantees the reliability of apps, maximizes cost savings (across storage, compute, and users), and improves productivity in a self-service DataOps environment. Unravel Data supports all big data applications such as ETL, analytics, machine learning, SQL and streaming, running on popular Big Data systems such as Hadoop and Spark for both on-premise and cloud environments. Customers include leading Big Data practitioners such as Autodesk and YP.com.