Systems | Development | Analytics | API | Testing

Apache Parquet has become the de-facto standard for storing data used in analytics workloads, and has seen very broad adoption as a free and open-source storage format. When used as the underlying storage layer for Apache Iceberg, Parquet is also a foundational building block in modern lakehouse architectures, which enable warehouse-like capabilities on cost effective object storage. Let’s take a closer look at what Parquet actually is, and why it matters for big data storage and analytics.

In a technologically dominated world, producing top-notch software isn’t merely a competitive edge – it’s a must. Whether creating a mobile application, a website, or a large-scale enterprise system, consumers anticipate that your software be secure, responsive, and flawless. That’s where Quality Assurance (QA) Testing comes in. It doesn’t just make your software work – it work well, do what users need it to do, and meet world-class standards of excellence.

At Bitrise, we continually invest in security best practices to ensure that our customer’s data stays safe and secure. As a part of an on-going effort, we are excited to announce that we’ve successfully completed our SOC 2 report. The examination was conducted by A-LIGN, a technology-enabled security and compliance firm trusted by more than 4,000 global organizations to help mitigate cybersecurity risks.

The software and product life cycle is fraught with pitfalls and tradeoffs. While testing applications under production-like load is critical to ensuring the reliability, performance, and security of your data storage and software services, you need to do this testing without actually affecting the production data and systems. In essence, you have to pull off the impossible – be as close to production as you can without actually being production.

EU-based organizations, particularly those in regulated sectors such as Financial Services, Energy, and Telecommunications, are required to store and process data strictly within the EU to legally comply with regulatory frameworks such as the General Data Protection Regulation (GDPR).

Delivering analytics quality at a global scale is never easy. One broken event or missed signal can derail product launches, fuel bad decisions, and shatter customer trust overnight.

The AI agent revolution is transforming how we work, but most analytics platforms are stuck in the past—forcing you to context-switch between your agents and separate BI tools to get data insights. This fragmented approach creates friction, breaks workflows, and ultimately slows down decision-making. When speed matters most, you need your AI agents to seamlessly access and analyze enterprise data without the traditional barriers of maintaining custom integrations and limited API functionality.

Imagine you’re closing a big deal with a Fortune 500 client. Everything looks good until they ask, “Are you SOC 2 compliant?” If you can’t answer with confidence, that deal might slip away. By 2025, with a threat landscape that evolves daily and customer trust is challenging to acquire, SOC 2 compliance has become the new baseline for doing business for SaaS, cloud services, fintech, and digital health vendors.

It’s 2 AM. Your release just broke again. CI pipelines were green, tests appeared clean, and the dashboard looked harmless. Yet, staging is down, and no one knows why. You're staring at static HTML reports and generic error logs. They show what failed, but give no clue why, no context, no trace, no help. It's like debugging in the dark. This is what outdated test reporting costs: lost hours, broken releases, and reactive firefighting when you should be sleeping or shipping.

If your organization has a complex Oracle deployment, or you are on a modernization journey — migrating to the cloud, preparing quarterly updates, or consolidating systems, you already know the stakes are high. Oracle systems and transformations are strategic, complex, and costly. But too often, they’re derailed by one silent saboteur: outdated, manual testing.