Get started with the Data Client Library

The Data Client Library provides Scala/Java libraries that you can use in your
projects to access the HERE platform. The Data Client Library relies on the
Pekko Streams implementation of the Reactive Streams standard, which provides
abstractions for building end-to-end streaming data processing libraries.

The Data Client Library contains the following main modules:

data-engine -- Provides higher level abstractions to interact with data.
spark-support -- Provides utilities to connect Spark with HERE platform
data.
flink-support -- Provides utilities to run Data Client Library within Flink
Jobs.

Choose the level of abstraction that best suits your application. Typically,
low-level APIs provide more flexibility than high-level APIs, but you may need
to write more application code.

The use of the Data Client Library requires a basic understanding of some
concepts related to the HERE platform. For explanations of these concepts, see
the
Data API Developer Guide.

The use of the Data Client Library requires the basic understanding of following
libraries:

Typesafe Config

For scala developers:

Pekko Stream

For java developers:

For the terms and conditions covering this documentation, see the
HERE Documentation License.

Data privacy is of fundamental importance to HERE and our customers. We practice
data minimization and don’t collect data we don’t need. And we promote
pseudonymity for data subjects wherever a service does not require personal
information to function. We employ privacy by design in services we develop. We
strive to go beyond mere regulatory compliance and make privacy an integral part
of our corporate culture. We believe that our approach to privacy is vital to
earning and retaining the trust of our customers – and the bedrock of our future
success as a data-driven location platform.

For more information on how data privacy is of fundamental importance to HERE
and our customers, see the
HERE Privacy Charter.

For more information on HERE data security and durability best practices, see
the Data API.