The open-source data landscape is undergoing a significant transformation, driven by a collective industry push toward vendor neutrality, cost management, and the rapid adoption of artificial intelligence workloads.
Reflecting on this evolving journey, Linux Foundation Research and the OpenSearch Software Foundation have jointly published The 2026 Open Data Infrastructure Report. The comprehensive study examines how modern organizations are building out their core data infrastructure, evaluating the strategic factors influencing their technology choices, and assessing the expanding role that OpenSearch plays within their broader enterprise architectures.
The release of the report marks a notable milestone for OpenSearch, which originally began as an open alternative built by Amazon Web Services under the Apache 2.0 license after Elastic relicensed Elasticsearch and Kibana in 2021. Three years after that initial fork, the project transitioned into a neutral governance model when the Linux Foundation launched the OpenSearch Software Foundation in September 2024 as its official, vendor-neutral steward.
Conducted in May 2026, the newly published survey captures insights from 294 respondents across diverse industry categories, including IT vendors, enterprise end-user organizations, and independent technical consultants. The findings paint a detailed picture of an enterprise market that is increasingly prioritizing architectural flexibility, cost predictability, and independence from single-cloud ecosystems.
The Report Briefly: AI Adoption and OpenSearch’s Market Trajectory
Generative AI and large language model (LLM) powered applications have firmly established themselves as the dominant enterprise use cases, cited by 82% of the organizations surveyed. Across every global region, at least 83% of respondents reported that they are already running active AI workloads or have concrete plans to deploy them in the near future.
Within this booming AI landscape, OpenSearch has captured a meaningful footprint. Among current OpenSearch users, 62% report utilizing the platform for AI-related workloads, with 44% of those users categorizing it as core AI infrastructure rather than a mere supporting or peripheral component.
Market awareness and production usage of OpenSearch have also experienced steady growth. By 2026, 89% of surveyed organizations reported that they had heard of OpenSearch, representing a substantial increase from 68% just two years prior. Concurrently, active production deployments climbed from 19% to 36% over the same timeframe, while another 36% of organizations noted that they are actively running tests or assessing adoption.
When organizations evaluate data infrastructure platforms, cost considerations and vendor independence emerge as the paramount decision-making factors. Total cost of ownership tops the selection criteria for 80% of organizations, closely followed by security and compliance requirements at 79%, and vendor independence at 69%. Furthermore, 71% of respondents indicated that running their technical infrastructure entirely outside the direct control of any single cloud provider is a strategic priority for their enterprise. Across the entire sample, the average annual data infrastructure spend sits at approximately $2.4 million, underscoring the substantial financial stakes involved in these architectural decisions.
Among active users, traditional search and retrieval workloads remain the most common use case at 91%, followed by log analytics and observability at 83%, real-time analytics at 70%, and AI-related workloads at 62%. Additionally, hybrid search has become the preferred approach for 68% of organizations navigating complex information retrieval challenges.
What Now for OpenSearch and the Open Data Layer?
Despite healthy growth and rising awareness, the report reveals that most current OpenSearch deployments are not yet deeply entrenched within enterprise workflows. Six in ten users report that their OpenSearch setup remains experimental or flexible enough that it could be swapped out relatively easily, with only 36% describing their deployment as deeply embedded or mission-critical. Among non-users, while 81% express openness to evaluating the platform, only 14% have active plans to do so.
Alongside the publication of the report, the OpenSearch Software Foundation announced three new additions to its membership roster. Most notably, Intel has joined the foundation, alongside two new long-term support vendors aimed at bolstering enterprise confidence and stability.
Discussing the broader trajectory of the technology stack and the strategic positioning of OpenSearch, Bianca Lewis, Executive Director of the OpenSearch Foundation, noted the shifting dynamics of enterprise AI infrastructure.
"The technology stack powering agentic AI is shifting rapidly, and with growing uncertainty around AI costs, long-term commitments to proprietary platforms present both a financial and architectural risk," Lewis said. "Now, leaders are turning to an open, vendor-neutral platform to strategically mitigate risk."
Lewis emphasized that an open data layer provides vital cost visibility and granular insight into which underlying services are being called, giving engineering teams the clarity required to accurately forecast, budget, and manage their infrastructure spend.
"This delivers the flexibility to innovate without vendor lock-in, ensuring organizations maintain sovereignty over both their data and their spend as the future of AI takes shape," Lewis added.
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