StreamSets announced support for processing change data capture (CDC) information from deployments using Oracle Data Guard.
The support for this additional data source provides a reliable and efficient method for building data integration pipelines using CDC on production databases.
CDC allows data engineers to capture and propagate changes made to databases in near real-time, reducing the time needed to make new data available for analysis. This capability is essential for frequently-updated data or for low-latency data replication scenarios.
With StreamSets, data engineers can perform CDC information from Oracle Data Guard as an efficient means to replicate and synchronize data to cloud destinations such as Snowflake or AWS to perform reporting and analytics.
“Keeping up with the fast-paced demands of today’s data-driven world requires real agility,” said Dima Spivak, COO Products at StreamSets. “Organizations must be able to access, replicate, and synchronize their data securely and efficiently. This latest enhancement to our platform makes that easier than ever before.”
As a disaster recovery solution, Oracle Data Guard allows data engineers to keep a standby database in sync with the primary database in case of primary database failure, minimizing the risk of data loss and reducing recovery time, which is essential for business-critical systems.
For StreamSets users, this new capability allows users to replicate and synchronize data efficiently and ensure high availability in case of failures, which is a critical consideration when building CDC pipelines on production databases. These same pipelines can be leveraged with modern data platforms such as Snowflake to streamline reporting and enable analytics for data driven-decision making.
The Latest
Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...
Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...
For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...
New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...
Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...
In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ...
In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...
When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...
Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...
Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...