PostgreSQL
Consistent relational data and transactions.
Dependable AI needs a solid data foundation. We own the whole stack, across databases, streaming and machine-learning frameworks.

We choose data technologies by access pattern and load: PostgreSQL for transaction-safe, ACID-compliant models, MongoDB for flexible schemas, Elasticsearch for search in the millisecond range. For real-time we use Apache Kafka and Spark Structured Streaming, and prediction models are built with TensorFlow or PyTorch.
Storage by need
PostgreSQL for relational data, MongoDB for document-based data, Elasticsearch for search.
Data streams
Apache Spark and Kafka for batch and real-time processing.
Machine Learning
TensorFlow and PyTorch for deep learning and production models.
Foundation first
Reliable pipelines and a clean warehouse as the basis.

Deep-learning frameworks for training and production models.

Distributed processing and streaming of large data volumes.

Relational and document-oriented storage by access pattern.

Full-text search and analysis over large data volumes without latency.

Cloud data warehouses with separated storage and compute.

Interactive dashboards and self-service analytics.
Sketch out your data sources and access patterns: we design the stack across storage, streaming and modelling, and lay the groundwork that AI predictions can stand on.
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