Systems | Development | Analytics | API | Testing

Independent Software Vendors (ISVs) must continuously differentiate their offerings to thrive in today’s competitive SaaS market. Customers have high expectations and often carry a healthy dose of skepticism when a new vendor claims to deliver “the best solution” for productivity, cost savings, and revenue growth. To break through this status quo and deliver true value, ISVs need to provide smart, scalable, and secure solutions—faster than the competition.

Boost query performance by more than 2.5X and reduce storage costs by 50% compared to self-tuned Hive tables, without lifting a finger. Many data teams still need to manually develop and schedule custom tasks to maintain each and every table in their lakehouse, leading to inconsistent query performance and runaway costs.

The climate crisis is the defining challenge of our time, and cities are on the frontlines. Home to more than half of the world’s population, cities are both major contributors to global emissions and critical drivers of climate solutions. Delivering cleaner air, healthier communities, and resilient infrastructure requires not just commitment, but the power of data to guide and accelerate action.

A few months ago, at Qlik Connect, we announced the launch of Qlik Open Lakehouse, a new, fully managed capability that brings together the best of the Upsolver platform together with Qlik Talend Cloud. And today, we are excited to announce the general availability of Qlik Open Lakehouse within Qlik Talend Cloud that makes it easy and cost-effective for organizations to ingest, optimize, and manage massive amounts of data directly in Apache Iceberg–based lakehouses.

IT Professionals Day is our opportunity to celebrate the people who keep the digital world running - the ones who make sure data is secure, reliable, and ready to power innovation. At Qlik, we know IT professionals aren’t just solving problems, they’re enabling possibilities.

It’s been nearly three years since generative AI burst onto the scene, promising to revolutionize decision-making and operations for enterprises. The early days were all about visions and roadmaps; but now, boards and CFOs are demanding real ROI and measurable business impact from their investments.

We’re at a pivotal moment in the data integration market. For years, the rallying cry for data professionals was to adopt the "modern data stack" (MDS), with the promise of a "best-of-breed" approach. This vision led many organizations to assemble a collection of specialized, single-purpose tools—one for ingestion, another for transformation, a third for quality, and so on—to create a highly effective data environment. However, reality has proven far more complex.

Qlik’s partnership with Amazon Web Services (AWS) is at the very core of our cloud data integration and analytics platform. Think of it like the iconic double helix of DNA. Just as DNA’s intertwined strands carry the fundamental instructions for life, the interconnection between Qlik and AWS carries the innovation and reliability that power the future of enterprise analytics, data integration, and AI.

When comparing Apache Parquet and Apache Iceberg, we need to first understand the differences between file formats and table formats. Parquet is a file format, whereas Iceberg is a table format. File formats focus on efficient storage and compression of data. They define how the raw bytes representing records and columns are organized and encoded on disk or in a distributed file system such as Amazon S3. The Parquet file format has become the de-facto standard for storing data used in analytics workloads.

Apache Iceberg is transforming how organizations build and manage their data infrastructure, enabling lakehouse architectures that combine the best of data lakes and data warehouses. In this blog, we look at five real-world implementations demonstrate Iceberg's versatility and the advantages it brings to modern data management challenges. Learn more about Data Lakehouses.