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GigaSpaces Partners with Informatica on Digital Integration Hub

GigaSpaces partnered with Informatica to deliver an Intelligent Digital Integration Hub across cloud, on-premise and hybrid environments.

The solution unifies Informatica's Hybrid Integration Platform including: Integration Hub and Cloud iPaaS, together with GigaSpaces InsightEdge in-memory real-time analytics and machine learning platform within the Digital hub.

Applications across the enterprise can now leverage timely, trusted data and real-time analytic insights for faster, smarter business decisions. Informatica Integration Hub uses a publish/subscribe model and allows self-service consumption of data by any user or application. GigaSpaces InsightEdge, as a transactional and analytical processing speed layer, analyzes any data model (text, objects, documents, images, etc.) and enriches the hub with event-driven machine and deep learning capabilities on both mutable streaming and hot data simultaneously with historical data on data lakes. These insights can instantly be shared with applications and existing systems.

The solution leverages Informatica's Enterprise Data Catalog (EDC), powered by the Informatica CLAIRE engine, to provide machine-learning-based discovery to scan, catalog and detect data assets across the enterprise.

Together, GigaSpaces and Informatica Intelligent Digital Integration Hub is used to:

- Accelerate hybrid data integration and analytics on any data model including structured, unstructured and semi-structured data

- Orchestrate complex transactional and analytical processing with a persistence layer that can be used as a transient or as a sync layer

- Facilitate self-service consumption of data and insights

- Decouple source and target applications, allowing easy consumption by users and reduce load on sources systems

- Enable multi-latency integration with advanced orchestration and scheduling for batch and API's driven data

- Support extreme performance and rich machine and deep learning capabilities; including Spark, numeric computing via Tensor and loading of pretrained Caffe or Torch models, as well as various NLP, OCR, Text Classification, image recognition and other libraries

- Integrate multiple clouds, new enterprise applications, in-memory speed layer and data lakes, with existing systems

- Provide visibility, control, monitoring, and alerting across all data workflows

Benefits for the enterprise include:

- Superb user experience: with low latency response times, especially at critical traffic peaks

- Optimized TCO: allowing the system of record applications to be planned for standard usage and not peaks

- High agility: microservices architecture to rapidly develop and deploy new applications

- 24/7 always on: Market proven, high availability for enterprise grade mission critical applications

- Real-time Insights to Action: Analytics and machine learning run on live mutable data and simultaneously on historical data for time-sensitive decisions and actions

Ronen Schwartz, SVP and GM, Cloud, Big Data, Data Integration, at Informatica. "Our integration with GigaSpaces InsightEdge enables our customers to reduce the cost and complexity of data and APIs while achieving high performance at large scale."

Additional applications which are fueled by the solution include real-time fraud detection, live risk management, predictive maintenance, dynamic pricing, personalized recommendations, supply chain management and more.

"Together Informatica and GigaSpaces, are powering stronger, innovative enterprises as they continue to add new data-driven applications to remain competitive," said Yoav Einav, VP of Products for GigaSpaces. "The Intelligent Digital Integration Hub tames complex hybrid integration environments with extreme performance, agility, availability and the ability to deliver real time actionable insights, helping customers optimize operations, improve regulatory compliance and enhance customer experiences."

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GigaSpaces Partners with Informatica on Digital Integration Hub

GigaSpaces partnered with Informatica to deliver an Intelligent Digital Integration Hub across cloud, on-premise and hybrid environments.

The solution unifies Informatica's Hybrid Integration Platform including: Integration Hub and Cloud iPaaS, together with GigaSpaces InsightEdge in-memory real-time analytics and machine learning platform within the Digital hub.

Applications across the enterprise can now leverage timely, trusted data and real-time analytic insights for faster, smarter business decisions. Informatica Integration Hub uses a publish/subscribe model and allows self-service consumption of data by any user or application. GigaSpaces InsightEdge, as a transactional and analytical processing speed layer, analyzes any data model (text, objects, documents, images, etc.) and enriches the hub with event-driven machine and deep learning capabilities on both mutable streaming and hot data simultaneously with historical data on data lakes. These insights can instantly be shared with applications and existing systems.

The solution leverages Informatica's Enterprise Data Catalog (EDC), powered by the Informatica CLAIRE engine, to provide machine-learning-based discovery to scan, catalog and detect data assets across the enterprise.

Together, GigaSpaces and Informatica Intelligent Digital Integration Hub is used to:

- Accelerate hybrid data integration and analytics on any data model including structured, unstructured and semi-structured data

- Orchestrate complex transactional and analytical processing with a persistence layer that can be used as a transient or as a sync layer

- Facilitate self-service consumption of data and insights

- Decouple source and target applications, allowing easy consumption by users and reduce load on sources systems

- Enable multi-latency integration with advanced orchestration and scheduling for batch and API's driven data

- Support extreme performance and rich machine and deep learning capabilities; including Spark, numeric computing via Tensor and loading of pretrained Caffe or Torch models, as well as various NLP, OCR, Text Classification, image recognition and other libraries

- Integrate multiple clouds, new enterprise applications, in-memory speed layer and data lakes, with existing systems

- Provide visibility, control, monitoring, and alerting across all data workflows

Benefits for the enterprise include:

- Superb user experience: with low latency response times, especially at critical traffic peaks

- Optimized TCO: allowing the system of record applications to be planned for standard usage and not peaks

- High agility: microservices architecture to rapidly develop and deploy new applications

- 24/7 always on: Market proven, high availability for enterprise grade mission critical applications

- Real-time Insights to Action: Analytics and machine learning run on live mutable data and simultaneously on historical data for time-sensitive decisions and actions

Ronen Schwartz, SVP and GM, Cloud, Big Data, Data Integration, at Informatica. "Our integration with GigaSpaces InsightEdge enables our customers to reduce the cost and complexity of data and APIs while achieving high performance at large scale."

Additional applications which are fueled by the solution include real-time fraud detection, live risk management, predictive maintenance, dynamic pricing, personalized recommendations, supply chain management and more.

"Together Informatica and GigaSpaces, are powering stronger, innovative enterprises as they continue to add new data-driven applications to remain competitive," said Yoav Einav, VP of Products for GigaSpaces. "The Intelligent Digital Integration Hub tames complex hybrid integration environments with extreme performance, agility, availability and the ability to deliver real time actionable insights, helping customers optimize operations, improve regulatory compliance and enhance customer experiences."

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In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

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