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New Version of StreamSets Data Collector Released

StreamSets Inc. announced the latest release of StreamSets Data Collector, continuous ingest software that automatically addresses the problem of data drift.

The new release helps enterprises accelerate their time to insights by proactively managing the completeness, accuracy and consistency of their data as it flows from collection to consumption.

“Given the siloed, yet strategic nature of data, enterprises must develop a culture of data performance management,” said Girish Pancha, CEO, StreamSets, Inc. “Just as network operations and security operations matured from numerous siloed projects into centers of excellence, we believe it is time for data operations to make that same critical leap. StreamSets was founded to build the cornerstone infrastructure upon which enterprises can institute disciplined performance management for their data-in-motion.”

With its latest v1.2 release, StreamSets Data Collector automates data drift handling and now supports the Big 3 major Hadoop distributions from Cloudera, MapR and Hortonworks. This version also is certified with the MapR Converged Data Platform including extended support for MapR Streams. It also provides connectors for other popular big data technologies such as Elasticsearch, NoSQL databases such as MongoDB and Cassandra and transient stores such Apache Kafka, MapR Streams and JMS-compliant message queues.

StreamSets Data Collector gives enterprises the necessary control, efficiency and agility to effectively manage performance of their data flows.

- Data flow KPIs for real-time control: Uniquely, StreamSets Data Collector monitors, detects and acts on changes in data patterns alongside providing fine-grained metrics on data flow throughput, latency and error rates. Data drift-handling rules ensure that pipelines flow correctly even when schema changes. Threshold rules, alerts and plug-in processors combine to identify, filter, re-route and sanitize anomalies in-stream to ensure that data lands ready for consumption.

- Adaptable pipelines for efficiency: StreamSets Data Collector provides a visual (integrated development environment) IDE for the design and execution of intent-driven data flows with minimal schema specification and custom code. It is a highly flexible environment, handling both batch and streaming data, and deploying on edge nodes, natively in clusters and as part of an application stack.

- Containerized architecture for agility: Built for continuous operations, StreamSets Data Collector addresses the issues of constant infrastructure upgrades and data flow evolution head on. Each source, stage and destination in a pipeline is isolated, allowing you to maintain and modernize your data infrastructure while ensuring zero downtime.

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New Version of StreamSets Data Collector Released

StreamSets Inc. announced the latest release of StreamSets Data Collector, continuous ingest software that automatically addresses the problem of data drift.

The new release helps enterprises accelerate their time to insights by proactively managing the completeness, accuracy and consistency of their data as it flows from collection to consumption.

“Given the siloed, yet strategic nature of data, enterprises must develop a culture of data performance management,” said Girish Pancha, CEO, StreamSets, Inc. “Just as network operations and security operations matured from numerous siloed projects into centers of excellence, we believe it is time for data operations to make that same critical leap. StreamSets was founded to build the cornerstone infrastructure upon which enterprises can institute disciplined performance management for their data-in-motion.”

With its latest v1.2 release, StreamSets Data Collector automates data drift handling and now supports the Big 3 major Hadoop distributions from Cloudera, MapR and Hortonworks. This version also is certified with the MapR Converged Data Platform including extended support for MapR Streams. It also provides connectors for other popular big data technologies such as Elasticsearch, NoSQL databases such as MongoDB and Cassandra and transient stores such Apache Kafka, MapR Streams and JMS-compliant message queues.

StreamSets Data Collector gives enterprises the necessary control, efficiency and agility to effectively manage performance of their data flows.

- Data flow KPIs for real-time control: Uniquely, StreamSets Data Collector monitors, detects and acts on changes in data patterns alongside providing fine-grained metrics on data flow throughput, latency and error rates. Data drift-handling rules ensure that pipelines flow correctly even when schema changes. Threshold rules, alerts and plug-in processors combine to identify, filter, re-route and sanitize anomalies in-stream to ensure that data lands ready for consumption.

- Adaptable pipelines for efficiency: StreamSets Data Collector provides a visual (integrated development environment) IDE for the design and execution of intent-driven data flows with minimal schema specification and custom code. It is a highly flexible environment, handling both batch and streaming data, and deploying on edge nodes, natively in clusters and as part of an application stack.

- Containerized architecture for agility: Built for continuous operations, StreamSets Data Collector addresses the issues of constant infrastructure upgrades and data flow evolution head on. Each source, stage and destination in a pipeline is isolated, allowing you to maintain and modernize your data infrastructure while ensuring zero downtime.

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2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...

In March, New Relic published the State of Observability for Media and Entertainment Report to share insights, data, and analysis into the adoption and business value of observability across the media and entertainment industry. Here are six key takeaways from the report ...

Regardless of their scale, business decisions often take time, effort, and a lot of back-and-forth discussion to reach any sort of actionable conclusion ... Any means of streamlining this process and getting from complex problems to optimal solutions more efficiently and reliably is key. How can organizations optimize their decision-making to save time and reduce excess effort from those involved? ...

As enterprises accelerate their cloud adoption strategies, CIOs are routinely exceeding their cloud budgets — a concern that's about to face additional pressure from an unexpected direction: uncertainty over semiconductor tariffs. The CIO Cloud Trends Survey & Report from Azul reveals the extent continued cloud investment despite cost overruns, and how organizations are attempting to bring spending under control ...

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According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...