The tools behind the platforms we build

What each tool is genuinely good at, where it fits in an enterprise architecture, and when we would tell you to use something else.

An engine for processing data across many machines, using the same code whether the data is small or large.

A distributed log where records are appended and kept, so many consumers can read them at their own pace.

Amazon's cloud platform, offering a large range of services for computing, storage, databases and more.

A data catalogue that records what data exists and observes how it is actually queried to inform what it shows.

An open source platform for building, scheduling and monitoring batch data workflows written in Python.

An open source platform for exploring data, building charts and publishing dashboards over any database it can connect to.

A data workspace that brings cataloguing, lineage and collaboration together where the data team already works.

An Azure service bringing warehouse queries, Spark processing and data integration together in one workspace.

An open source metadata and governance framework built for Hadoop platforms, with a type system you extend.

Not sure which tool fits your problem?

We will tell you when the answer is the one you already have.