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Chronicles

The story behind the story

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EMC's Pivotal open sources big data tech, joins newly formed Hadoop-focused Open Data Platform with Hortonworks, IBM, GE, Verizon, Infosys, others

Pivotal open sources its Hadoop and Greenplum tech, and then some  —  Pivotal CEO Paul Maritz at Structure Data 2014. Credit: Pivotal CEO Paul Maritz / Jakub Mosur

Gigaom Derrick Harris

Context & Ripple Effects

In 2015 Pivotal — the EMC/VMware spinout built around big-data and PaaS software — gave away its crown jewels: it open sourced its Hadoop distribution and Greenplum database tech, then joined the newly formed Open Data Platform alongside Hortonworks, IBM, GE, Verizon and Infosys. The move reads as a coalition play: rather than compete on a proprietary Hadoop fork, Pivotal bets that a standardized, vendor-neutral core attracts more enterprise buyers than any single distribution.

That bet carried the company through its subsequent financing arc — the $653M Series C in 2016, the IPO filing in 2018, and a first day of trading that valued it around $3.8B — though the related coverage of disappointing Hadoop-era exits shows where the underlying market ultimately went.

First-order effects

  • Enterprises evaluating big-data infrastructure gain a common, multi-vendor core — Pivotal, Hortonworks, IBM, GE, Verizon and Infosys now commit to interoperable Hadoop rather than competing distributions.
  • Pivotal's differentiation shifts immediately: with its Hadoop and Greenplum code freely available, its commercial case rests on services and upper-layer software instead of license lock-in.

Second-order effects

  • The Open Data Platform's roster — spanning hardware (GE), telecom (Verizon), IT services (Infosys) and software (IBM) — pressures any Hadoop distributor left outside the alliance to join or justify a divergent stack to shared customers.
  • For parent EMC, an open-sourced Pivotal becomes a cleaner asset for the standalone company that later files to go public, since revenue no longer depends on defending a proprietary fork.

Third-order effects

  • The pattern this foreshadows — open-sourcing core infrastructure while monetizing services above it — proved fragile: by late 2019, Hadoop-focused startups had seen disappointing exits and Pivotal itself was cited as evidence that public clouds hollow out business models built on self-hosted open source.
  • If platform-level value migrates to whoever operates the infrastructure rather than whoever licenses it, vendor coalitions like the ODP become staging grounds for consolidation rather than durable moats.

The trend: Enterprise data platforms are moving from proprietary distributions toward open-source coalitions — and, per the later Hadoop-era outcomes, then toward absorption by public-cloud operators who commoditize what the coalitions standardized.