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Clustrix Releases ClustrixDB 7.0

Clustrix announced availability of ClustrixDB release 7.0.

The company expanded the boundaries of relational database elasticity with a scale-out, shared-nothing ACID-compliant architecture that massively scales both reads and writes, and can be deployed in any cloud or data center. Now it has taken its product to the next level. With, on average, 30 percent performance improvements, an enhanced “Flex” option and new reporting to better understand workload and query times, 7.0 enables companies to easily and economically adjust database capacity to handle steep fluctuations in demand.

According to Mike Azevedo, President & CEO of Clustrix, this release comes just in time to help e-commerce site owners avoid slowdowns and downtime over the busy holiday season. “Today, when online shoppers have more consumer power than ever before, retailers must be able to focus on attracting and retaining customers. They don’t have time to worry about the database under the hood of their e-commerce platform, and the last thing they need to hear is that customers are experiencing delays. With ClustrixDB 7.0, e-commerce merchants have even more scale and a much easier and faster way to prepare for high holiday traffic and checkouts.”

ClustrixDB Flex allows companies to effortlessly navigate seasonal, promotional or other spikes, while sidestepping the need to pay for capacity all year long. By making it even easier to leverage ClustrixDB’s Flex option, release 7.0 allows merchants, for example, to easily scale up their ClustrixDB cluster to handle peak holiday workloads with just a few clicks, and then scale back down post-holiday, paying for capacity only as needed.

ClustrixDB delivers scalable performance and capacity in the data center or the cloud. While the cloud enables unprecedented resource elasticity, traditional SQL databases are limited to scaling “up” by moving the database to a larger instance, and do not support the ability to scale “out” the relational database with incremental additions of hardware resources. Only ClustrixDB gives the scale-out capabilities of a NoSQL database with the ACID and relational power of a SQL database. “Companies requiring high levels of online transaction processing need to leverage the reliability of ACID-compliant SQL, yet in doing so, they face tremendous scalability challenges without ClustrixDB,” said Azevedo. “ClustrixDB brings the consistency of SQL, yet the ability to scale to the exponentially increasing data demands that companies are experiencing today.”

ClustrixDB addresses this need with a SQL solution that is built for the cloud, and scales both reads and writes. ClustrixDB is a scale-out SQL database that can be deployed in any cloud, including: Rackspace, Microsoft Azure, ZeroLag and AWS.

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Clustrix Releases ClustrixDB 7.0

Clustrix announced availability of ClustrixDB release 7.0.

The company expanded the boundaries of relational database elasticity with a scale-out, shared-nothing ACID-compliant architecture that massively scales both reads and writes, and can be deployed in any cloud or data center. Now it has taken its product to the next level. With, on average, 30 percent performance improvements, an enhanced “Flex” option and new reporting to better understand workload and query times, 7.0 enables companies to easily and economically adjust database capacity to handle steep fluctuations in demand.

According to Mike Azevedo, President & CEO of Clustrix, this release comes just in time to help e-commerce site owners avoid slowdowns and downtime over the busy holiday season. “Today, when online shoppers have more consumer power than ever before, retailers must be able to focus on attracting and retaining customers. They don’t have time to worry about the database under the hood of their e-commerce platform, and the last thing they need to hear is that customers are experiencing delays. With ClustrixDB 7.0, e-commerce merchants have even more scale and a much easier and faster way to prepare for high holiday traffic and checkouts.”

ClustrixDB Flex allows companies to effortlessly navigate seasonal, promotional or other spikes, while sidestepping the need to pay for capacity all year long. By making it even easier to leverage ClustrixDB’s Flex option, release 7.0 allows merchants, for example, to easily scale up their ClustrixDB cluster to handle peak holiday workloads with just a few clicks, and then scale back down post-holiday, paying for capacity only as needed.

ClustrixDB delivers scalable performance and capacity in the data center or the cloud. While the cloud enables unprecedented resource elasticity, traditional SQL databases are limited to scaling “up” by moving the database to a larger instance, and do not support the ability to scale “out” the relational database with incremental additions of hardware resources. Only ClustrixDB gives the scale-out capabilities of a NoSQL database with the ACID and relational power of a SQL database. “Companies requiring high levels of online transaction processing need to leverage the reliability of ACID-compliant SQL, yet in doing so, they face tremendous scalability challenges without ClustrixDB,” said Azevedo. “ClustrixDB brings the consistency of SQL, yet the ability to scale to the exponentially increasing data demands that companies are experiencing today.”

ClustrixDB addresses this need with a SQL solution that is built for the cloud, and scales both reads and writes. ClustrixDB is a scale-out SQL database that can be deployed in any cloud, including: Rackspace, Microsoft Azure, ZeroLag and AWS.

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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 ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.