what is the databricks lake house
platform
databricks and the databricks lake house
platform
in this video you'll learn about
databricks and the databricks lake house
platform you'll also learn how to define
the databricks lighthouse platform give
examples of how to solve Big Data
challenges
and describe how it benefits data
practitioners
databricks was founded in 2013 By the
original creators of Apache spark Delta
Lake and ml flow
as the world's first and only lake house
platform in the cloud databricks
combines the best of data warehouses and
data Lakes to offer an open and unified
platform for data and AI
databricks is the inventor and Pioneer
of the data lake house architecture
coining the term in the research paper
lake house a new generation of open
platforms that unify data warehousing
and advanced analytics co-authored by
the databricks founders UC Berkeley and
Stanford University in 2021
the lake house Paradigm is designed as
the ideal data and AI platform for all
data types that is open with a single
security and governance model not only
is it designed to manage all data types
but it is cloud agnostic so data can be
governed wherever it is stored because
its purpose is to support all major data
and AI workloads teams can easily
collaborate and access all the data they
need to keep innovating and improving
all of these architectural features are
realized on the databricks lake house
platform including the reliability and
performance of Delta Lake as the data
Lake foundation
a fine-grained governance for data and
AI with unity catalog
and support for persona-based use cases
for all data team members the databricks
lake house platform architecture also
provides instant and serverless compute
where databricks provides and manages
the compute layer on behalf of the
customer
combining the best elements of data
warehouses such as reliability
governance and performance with the
openness and flexibility and machine
learning support of data Lakes the
databricks lighthouse platform is a
single platform that unifies data
warehousing and AI use cases this
unified approach eliminates the
challenges caused by previous data
environments such as data silos
complicated structures and fractured
governance and security structures
to reiterate the benefits of the data
lake house platform first it is simple
by providing a unified platform and
eliminating the complexity and expense
that stands in the way of achieving the
full potential of data analytics and AI
initiatives
it is open with a foundation on Delta
Lake for reliability and performance
while avoiding proprietary systems thus
making it easy to share data
unrestricted it allows you to build the
ecosystem you need with open source
projects and the vast network of
databricks Partners
and it is multi-cloud allowing you to
work on the cloud platform currently in
use with a consistent management
security and governance experience
The databricks Lakehouse platform
supports the workloads for data teams
including data warehousing data
engineering data streaming and data
science and machine learning
and speaking of Partners The databricks
Lakehouse platform provides the
flexibility to use your existing
infrastructure share your data and build
a modern data stack with unrestricted
access to open source data projects and
the broad databricks partner Network
including but not limited to those shown
here