The best solution for every challenge. We focus on stream data processing - with “Bespoke Data Engineering”.

Data Engineering from bakdata stands for new capabilities, faster actions, and reliable insights. Manageable, holistic and customer-centered.

Work

What we do


Data Streams

All data is a stream. We process your data as it emerges. We create streamlined, highly efficient and perfectly integrated stream data solutions. We build online algorithms that create valuable up-to-date information for you.

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Quick for Data Streams

Quick is our stream data application framework which unlocks your data streams for your application. It lets you integrate your algorithms seamlessly and provides them with modern APIs through GraphQL.

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Open Source

Our heart beats for coding. As part of the open source community, we benefit from open source projects such as Kafka or Kubernetes and develop our own open source projects.

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Talks

We appreciate the community and we share. We frequently report on ongoing projects and missions accomplished. As a team and together with you, we gave several talks.

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More recent work?
Send us an email!

info@bakdata.com

About

bakdata

bakdata stands for open, individual data solutions and holistic data concepts. Although we see ourselves as an IT service provider, we do not work for, but together with our customers.

With the need to further develop the concept of data management, the computer scientists Alexander Albrecht and Christoph Böhm combined their practical and scientific experience in administration, integration and analysis of large, complex volumes of data. With that, they laid the foundations for bakdata.

Since 2013, we have been working in our Berlin office to counteract non-coordinated and cost-intensive systems. Therefore, we consider classic technologies as well as the latest technology trends or open-source software. For us, “Bespoke Data Engineering” means using clever strategies to expose the added value in your data.

Services

Technics

Our services center around stream data processing and cover connected data systems from traditional commercial database systems of established providers to state-of-the-art open source software and in-house developments. We bundle highly-demanded expert knowledge with our core competence in the field of Data Engineering. We draw on many years of experience as well as on current standards from research, science and technology.

Using approaches from the fields of statistics, machine learning and knowledge management, we enable scalable solutions. For more efficiency and lower risks.

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Apache Kafka

Kafka Streams

Kafka Connect

Kubeflow

(No)SQL

PostgreSQL

Elasticsearch

GraphQL

Java

Python

Kotlin

Scala

Kubernetes

Amazon Web Services (AWS)

Google Cloud Platform (GCP)

Microsoft Azure

Team

Play

Alexander Albrecht
Managing Partner

Christoph Böhm
Managing Partner

Our team of 15+ best-in-class engineers creates Live Data Products for diverse industries, such as life science, healthcare, insurance, mechanical engineering, e-commerce and logistics. With analytical thinking and pragmatic working methods, we accompany and enable our customers to move on to the next stage of their own development. We are motivated by our enthusiasm for innovation. It is important for us to give space for development. At the same time, our work follows clear intentions. We combine pragmatism with quality and ingenuity.

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Jobs

Join our team

People with ideas. Creative minds passionately pursuing their goals. Innovators who significantly shape the future of data stream processing. Be a part of it.

Blog

News


Harnessing Interactive Queries v2 in Kafka Streams: A Practical Guide to Queries and State Stores

Interactive Queries enable access to Kafka Streams' state store. This article provides a structured overview and a running example of how to use it.

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Introducing KPOps

We introduce KPOps (Kafka Pipeline Operations), an open-source command-line app for deploying Apache Kafka data pipelines to Kubernetes.

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Contact

Say hi!

Office:
Hardenbergstraße 9B
10623 Berlin