THE ECOSYSTEM
Operating across the modern R&D stack.
DataJoint is the foundation between your lab systems and your data platforms. We don't replace the tools your team already runs. We make every one of them more reliable for science.
OUR APPROACH
We don't replace your stack. We make it more reliable for science.
Every platform in your R&D stack has a job. Lab systems capture what's done at the bench. Data platforms store and compute. AI tools build models. DataJoint sits upstream of all of them.
UPSTREAM OF EVERY PLATFORM
DataJoint is the layer between your labs and your data platforms. Source systems feed in. Codified scientific data flows out.
COMPLEMENTARY BY DESIGN
We integrate with the platforms your team already runs. No rip and replace. No competing analytics environment. No new warehouse.
MAKES EVERY TOOL MORE VALUABLE
Better inputs make every downstream platform more reliable for science: AI/BI, governance, analytics, all of it.
THE ECOSYSTEM
The platforms we run on. The ones we connect to.
DataJoint operates within the modern cloud and data platform infrastructure that R&D teams already trust.
BUILT ON
Cloud and infrastructure platforms DataJoint runs on.
INTEGRATES WITH
Data, lab, and AI platforms DataJoint connects to.
SOURCE SYSTEMS
What flows in.
DataJoint captures scientific data from every system that produces it. Instruments. Experimental records. Imaging. Clinical data. Raw storage. Every source carries its full context into the foundation.
Instruments & Assays
DataJoint captures raw experimental output.
Microscopes, electrophysiology rigs, behavioral apparatus, sequencers, and imaging systems generate multimodal data and metadata. DataJoint captures both: raw outputs alongside the subjects, sessions, parameters, instrument settings, and provenance that give the data meaning.
ELN / LIMS
DataJoint captures the computation behind the record.
ELN and LIMS systems capture what was done at the bench, including experimental metadata, sample tracking, and protocols. DataJoint captures the computation that produced the result, complementing this record with computational provenance and pipeline lineage.
Imaging & Omics
DataJoint codifies multimodal scientific data.
High-content imaging, transcriptomics, spatial omics, and proteomics generate enormous datasets with rich metadata. DataJoint codifies both the data and the metadata: acquisition parameters, sample identifiers, processing steps, and full pipeline lineage.
Clinical & CRO
DataJoint integrates external data with full governance.
Clinical data and CRO partnerships bring external scientific evidence into your R&D pipeline, alongside subject metadata, protocols, and study context. DataJoint preserves data integrity, metadata fidelity, and audit trails across institutional boundaries.
Raw Storage
DataJoint connects metadata to raw files.
Object storage and file systems hold raw experimental data. DataJoint keeps the files where they live and connects them to the structured metadata that gives them meaning.
Your Custom Systems
If it produces scientific data, DataJoint connects.
Custom instruments, in-house tools, lab-specific platforms, and existing data platforms (like Snowflake or Databricks acting as sources) all qualify. DataJoint's SciOps team builds integrations tailored to your environment, preserving full data integrity from source to result.
Want to talk?THE FOUNDATION BETWEEN
DataJoint codifies the science before it flows downstream.
Source systems generate data. Downstream platforms consume it. The foundation between is where experiments, pipelines, and results get codified as first-class scientific data.
DOWNSTREAM PLATFORMS
Where it goes.
Once the science is codified, it publishes downstream into the platforms running your AI, analytics, governance, and reporting. The foundation feeds everything you already invested in.
Data Lakehouses
DataJoint publishes governed scientific assets.
Store and query large-scale data. Provide compute for analytics and AI workloads. DataJoint reads existing organizational data from your lakehouse, applies computational workflows, and writes back governed scientific assets with full provenance intact.
AI · BI · Analytics
DataJoint makes downstream AI defensible.
Build dashboards, AI models, and reports on top of organizational data. DataJoint feeds them traceable scientific assets your AI can actually trust, with lineage and reproducibility intact.
Knowledge Graphs
DataJoint adds scientific context.
Knowledge graphs model the relationships between targets, compounds, patients, and outcomes. DataJoint feeds them the laboratory context they're missing: the actual experimental work, with all its parameters and provenance, connected to the entities the graph already knows.
ELN / Reports
DataJoint feeds back into the record.
Downstream consumer. DataJoint publishes governed, computationally-traceable artifacts back into the ELN/LIMS systems and documentation platforms your team uses for institutional memory.
Governance & Audit
DataJoint feeds them scientific provenance.
Data governance platforms catalog and control your data assets. DataJoint feeds them provenance and audit trails on scientific lineage, making audit trials, regulatory submissions, and compliance reviews defensible end to end.
Your Downstream Stack
DataJoint publishes wherever you need.
Beyond the standard data platforms, every R&D organization has internal tools, proprietary applications, and custom downstream systems. DataJoint exports governed scientific data into whatever consumes it, with full provenance intact.
Want to talk?PARTNERSHIP INQUIRIES
Building something that should work with DataJoint?
We work with platform partners, integration partners, and technology innovators across the life sciences R&D stack. If your platform serves scientific R&D and you're interested in exploring how DataJoint could complement it, we'd like to hear from you.
FREQUENTLY ASKED
Ecosystem and integration questions.
Common questions about how DataJoint fits with the platforms you already run. More answers on the full FAQ.
No. DataJoint sits upstream of these platforms and feeds them. Your existing platform investments become more valuable because they finally get scientifically coherent inputs from upstream experimental work. We’re complementary by design, not competitive.
ELNs and LIMS capture what was done at the bench: samples, protocols, inventory. DataJoint captures the computation that produced the result. Most pharma teams run both. We’re complementary, not overlapping. DataJoint can ingest from your ELN’s metadata layer and publish back the computational lineage your ELN can reference.
Both. DataJoint can pull existing organizational data from Databricks, Snowflake, and other lakehouse platforms, apply computational workflows to it, and deposit governed scientific assets back into the same environment. Many pharma R&D deployments run DataJoint as a round-trip layer between their lakehouse and their scientific work. The lakehouse becomes both source and sink, with DataJoint adding the scientific codification in between.
DataJoint exposes governed scientific data products that feed AI/BI tools natively. For Databricks customers, AI/BI Genie and ML workloads run on DataJoint-published assets with full provenance. For Snowflake customers, Cortex AI and BI tools consume from native tables. For Palantir customers, experimental work becomes Foundry objects with ontology relationships preserved.
Yes. DataJoint maintains active partnership relationships with leading data and life sciences platforms. For specific integration documentation, certified deployment patterns, and joint customer references, please reach out via the partnership contact below.
READY TO MAKE YOUR STACK MORE VALUABLE?