Transform how your team ingests, analyzes, and acts on data, without leaving PostgreSQL.
LakeHouse brings analytics, automation, and low-code workflows into a unified, scalable decision platform.
CYBERTEC LakeHouse for Scalefield is more than just a data platform. It is a full-stack, PostgreSQL-driven ecosystem designed to help you move from raw data to real decisions that is secure, scalable, and efficient.
Technical Foundation:
CYBERTEC LakeHouse is built on PostgreSQL and extended by CYBERTEC PostgreSQL Enterprise Edition (PGEE). This technical foundation enables high-performance processing through sharding and columnar storage, and supports both distributed aggregation for faster analysis and high availability by default. The platform offers a familiar, SQL-first interface that works for both small teams and enterprise-grade deployments. PostgreSQL gives you the core. PGEE takes it to the next level.
LakeHouse can be deployed in any infrastructure of your choice. For on-premises setups, it supports bare metal servers, virtual machines, and containerized environments like Kubernetes or OpenShift. If you prefer the cloud, deployment is seamless across AWS, Google Cloud, Azure, Huawei Cloud, MetalStack, and Alibaba. Hybrid models with mixed S3 or NAS storage are also supported. The Scalefield interface makes managing and scaling across these environments intuitive with a visual admin panel.
LakeHouse gives users flexible ways to interact with data and automation layers. Use the API to integrate with external services, the CLI for DevOps automation and scripting, or CYPEX - our low-code builder - to create full business workflows. Whether you are a power user or a non-technical team, access remains consistent, secure, and adaptable.
The data journey in LakeHouse is designed to be smooth, fast, and decision-ready. Users can ingest data from Oracle, MS SQL, Parquet files, and cloud buckets. Automation pipelines run via job schedulers and parallel processors. Once loaded, the data can be analyzed using PostgreSQL, Python, R, or pgvector, and finally, results are published or acted upon via dashboards and CYPEX workflows. It’s one system from ingestion to decision, without fragmentation.
Your team has uploaded logs, imported CSVs, and connected databases. The tables are full, but no one knows what to do next. You look up questions like “Why is this column empty?” or “How do I get JSON out of logs?” but most systems return nothing useful. CYBERTEC LakeHouse understands what you’re asking. It suggests relevant queries, explains patterns based on similar searches, and even hints at where your data may be broken or incomplete. This natural-language search layer transforms PostgreSQL into a conversational assistant that guides you through challenges with clarity.
A market analyst wants to explore trading activity over three years. She uploads the dataset, triggers anomaly detection with just a few clicks, and views historical outliers directly in her browser. Instead of manually building charts or exporting data to external tools, CYBERTEC LakeHouse delivers breakout trends in real time. From subtle pricing shifts to sharp spikes, the insights are ready in minutes, without writing a single query. Analysts can now move from raw CSV to confident insights faster than ever before.
A product team loads thousands of customer reviews into CYBERTEC LakeHouse to identify frustration points and improvement areas. The platform automatically applies semantic scoring, keyword clustering, and mood detection, all within PostgreSQL. There’s no need for external NLP libraries or data science support. In just one session, teams can spot which features users are unhappy with, when sentiment dropped, and how feedback varies across releases. The result is a shared understanding of what matters most to users and enables product decisions.
A data engineer uploads legacy Oracle exports in Parquet format to an S3 bucket. Typically, this would require shell access or a custom script. With LakeHouse, the files become instantly explorable. You can preview the schema, browse field metadata, and validate content directly through the interface. This reduces time spent on switching tools or asking DevOps for help. Now every team member can safely inspect structured files from cloud storage with audit trails and role-based access included by design.
A ride-share company wants to optimize operations using location data. They upload trip logs and instantly visualize ride volumes by hour and area. Built-in map support helps highlight peak demand zones, traffic bottlenecks, and underused regions. Instead of running static reports, the team interacts with live geographic patterns and quickly decides where to allocate resources or shift fleet operations. CYBERTEC LakeHouse turns geographic insight into a daily operational advantage without any GIS software.
A booking platform wants to understand how customer satisfaction varies across cities. Using built-in sentiment analysis tools, the team compares feedback from multiple locations and visualizes emotional trends over time. Whether it’s hotel reviews in Shanghai or transit comments from Berlin, LakeHouse clusters themes, detects tone shifts, and summarizes what users feel. This leads to targeted improvements, better marketing decisions, and smarter service rollouts tuned to regional needs instead of a generic global strategy.
CYBERTEC LakeHouse includes expert technical assistance during deployment, plus ongoing third-line support.
We also offer enhanced deployment and support packages, including fully managed and supported PostgreSQL on Scalefield.
Read the full CYBERTEC Scalefield online documentation for full overview and insights about the most powerful CYBERTEC DBaaS product.
CYBERTEC Scalefield includes expert technical assistance during deployment, plus ongoing
third-line support.
We also offer enhanced deployment and support packages, including fully managed and supported
PostgreSQL on Scalefield
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