Impetus Technologies, a big data software products and services company, announced the immediate availability of Visual Spark StudioTM, a new standalone tool aimed at addressing the increasing demand for Spark-based analytic and data processing solutions in enterprises. Visual Spark Studio is an Integrated Development Environment (IDE) that helps developers build, deploy and manage Apache Spark applications quickly and easily, in a matter of minutes.
Visual Spark Studio is a freely available product which has all of the capabilities required to build enterprise grade, Spark-based streaming and batch data processing applications with an intuitive drag-and-drop user interface. Within minutes, users can download it onto their desktop or server node, and start building and running Spark pipelines in local mode. These data pipelines can be exported for a full scale enterprise deployment using the StreamAnalytixTM platform. StreamAnalytix is an open-source enabled, enterprise-grade, multi-engine stream processing and machine learning platform which supports Apache Spark and Apache Storm as its core distributed processing engines with a future-ready architecture that allows the seamless addition of new engines like Apache Flink.
We have consistently received feedback from our enterprise customers on their growing usage of Spark and how the Visual Spark interface in StreamAnalytix dramatically increases their developer productivity. We decided to offer this tool as an additional quick-start product that anybody can download and use at no cost to accelerate their Spark learning and usage,” said Anand Venugopal, head of StreamAnalytix at Impetus Technologies. “We are particularly excited to share that Visual Spark Studio includes all of the capabilities to build and test functionally rich, enterprise-grade applications on an array of pre-built Spark operators. These applications can be easily deployed at full production scale using the Enterprise edition of the Impetus StreamAnalytix platform.”
Features of Visual Spark Studio
Visual Spark Studio is a lightweight development tool (less than 2GB on disk) that offers all of the necessary components and capabilities to quick-start Spark application development, including:
- A visual IDE to build, deploy, test and debug Spark 2.1 compliant applications that can be used individually or by small teams of developers collaboratively
- A rich array of drag-and-drop operators for data source, sink, transformation, and analytics
- Built-in dashboards for real-time data visualization
- A web-based tool with powerful multi-tenancy features that allow multiple users to connect to a single node
- Spark Operators:
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- Data generation – built-in data generator tool
- Channels – a rich array of data source connectors including Kafka, RDBMS, HDFS and more
- Processors – data enrichment, analytics and machine learning operators
- Emitters – data sink/write operators
- Platforms:
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- Available for Linux, iOS and Windows
Productivity tools like Visual Spark Studio are key to bridging the current high talent barrier blocking wider Spark adoption,” said Mike Matchett, senior analyst, Taneja Group. “The Impetus StreamAnalytix team is aiming to help enterprises accelerate competitive analytics application development, and, at the same time, control the engineering and operational costs associated with complex machine learning workflows.”
StreamAnalytix 3.1
StreamAnalytix enables enterprises to analyze and respond to events in real-time at Big Data scale using stream processing and machine learning. Supporting Apache Storm and Apache Spark in both batch and streaming modes, it not only includes Visual Spark Studio, but also a run-time DevOps platform for application monitoring and performance management. In July, Impetus introduced StreamAnalytix 3.1, which features a number of new capabilities, including:
- Rich Data Science Support – allows model training, testing and scoring on real time data. Also supports execution of H2O models and deep learning capabilities on TensorFlow.
- Integration of Python’s Rich Set of Utilities and Libraries.
- Missing-Data Imputation and Stream Correction Processors.
- Data Ingestion, Blending and Sink support now includes additional Amazon Web Services sources (AWS-IoT, AWS DynamoDB, Amazon SQS), Microsoft Azure (Event Hub, Blog Storage) and MongoDB.
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