Across the data ecosystem, a familiar pattern is emerging. Vendors are bringing more capabilities into a single platform, combining ingestion, transformation, storage, and governance under one umbrella. For some, this offers convenience and speed. For others, it introduces new challenges around flexibility, transparency, and long-term control.
The modern data stack once thrived on specialization. Independent vendors handled ingestion, transformation, and storage separately, giving data teams unprecedented choice. Now, the market is shifting back toward consolidation as large cloud and data platform providers extend beyond compute to capture more of the data lifecycle. What appears to simplify architecture often increases dependency and limits flexibility.
Compute remains the economic center of the ecosystem. Platforms that own it have an incentive to pull other layers closer, treating integration as a way to drive compute usage rather than as a strategic capability. That approach may scale their margins but reduces independence for customers.
At CData, we believe lasting value comes from preserving openness and giving customers control over how their data moves, where it lives, and how it performs.
Components: Building blocks for open integration
CData participates in the data integration ecosystem through open, standards-based components that work with every major cloud provider and data platform.
Ecosystem partnerships: Our technologies integrate across Microsoft, AWS, and Google environments. We participate in Microsoft SSIS and AWS Glue, and Google embeds CData connectivity directly in its products to simplify data access for Google Cloud users.
Connectivity: Enterprise-grade JDBC, ODBC, and Python drivers let developers build their own integrations directly into the systems they trust.
Data pipelines: CData Sync delivers secure, high-performance replication and Change Data Capture (CDC) across on-premises and cloud environments.
This component-first model lets customers assemble integration architectures that fit their needs rather than conforming to a single vendor framework. Composability gives enterprises freedom to evolve without disruption.
Choice: Control through openness
Across the industry, the line between open standards and vendor-managed SaaS is blurring. Openness must go beyond licensing to include how data moves, transforms, and is governed. Owning your data should mean owning the systems that manage it.
Many integration platforms still abstract away how and where data pipelines run, limiting visibility into execution and governance. Openness means having visibility into every stage of integration, how data moves, where it runs, and how it performs, rather than relying on black-box pipelines managed by a third party.
Control also means freedom of deployment. Enterprises should have the option to run integrations fully on-premises, in private cloud, or within their own environments, with complete oversight of credentials, governance, and performance.
Flexibility: Hybrid performance at scale
Even as cloud adoption accelerates, most organizations continue to operate hybrid data environments that include both legacy systems and modern platforms. The ability to move and synchronize data between these worlds remains essential for resilience and modernization.
Many mission-critical workloads still run on systems such as IBM DB2 iSeries, also known as AS400, which continue to support core business processes across industries. Integration platforms must connect these environments with modern analytics and AI systems without compromising security or uptime.
Advances in CDC and hybrid integration models now make it possible to replicate data from systems like DB2 iSeries into platforms such as Databricks, Snowflake, and Microsoft Fabric in near-real time. This enables teams to modernize infrastructure efficiently while preserving the reliability of systems that have supported the business for decades.
That balance between performance and completeness defines sustainable integration at scale. Across CData’s customer base, billions of records are replicated every month across mixed on-premises and cloud architectures, reflecting the confidence enterprises place in open, high-performance integration.
Transparent and predictable value
Predictable cost and transparent performance are key to long-term trust. Enterprises should be able to scale integration workloads without facing unpredictable usage costs or opaque licensing models. Pricing should align with clear business outcomes, not data volume or compute consumption.
As integration becomes a strategic capability, transparent value ensures teams can plan confidently and invest in the architectures that best serve their business.
A continued commitment to openness and trust
The return to platform consolidation may feel inevitable, but it is not universal. Most enterprises will continue to run hybrid workloads across multiple platforms and data stores. Many will discover that their platform of choice feels complete until they step outside its boundaries.
That is where CData provides lasting value, helping organizations integrate and govern data across environments that were never designed to work together.
The data integration landscape will keep evolving, but our focus remains the same: delivering open, flexible solutions that let customers decide how their data is accessed, moved, and managed. As consolidation reshapes the market, our guiding principle remains trust built on openness, transparency, and control.
Whether your center of gravity is in the cloud, on-premises, or somewhere in between, CData supports your architecture with the same principles that have guided us from the start: interoperability, transparency, and customer control.
