Compare the Top On-Premises Data Engineering Tools as of June 2025

What are On-Premises Data Engineering Tools?

Data engineering tools are designed to facilitate the process of preparing and managing large datasets for analysis. These tools support tasks like data extraction, transformation, and loading (ETL), allowing engineers to build efficient data pipelines that move and process data from various sources into storage systems. They help ensure data integrity and quality by providing features for validation, cleansing, and monitoring. Data engineering tools also often include capabilities for automation, scalability, and integration with big data platforms. By streamlining complex workflows, they enable organizations to handle large-scale data operations more efficiently and support advanced analytics and machine learning initiatives. Compare and read user reviews of the best On-Premises Data Engineering tools currently available using the table below. This list is updated regularly.

  • 1
    Peekdata

    Peekdata

    Peekdata

    Consume data from any database, organize it into consistent metrics, and use it with every app. Build your Data and Reporting APIs faster with automated SQL generation, query optimization, access control, consistent metrics definitions, and API design. It takes only days to wrap any data source with a single reference Data API and simplify access to reporting and analytics data across your teams. Make it easy for data engineers and application developers to access the data from any source in a streamlined manner. - The single schema-less Data API endpoint - Review and configure metrics and dimensions in one place via UI - Data model visualization to make faster decisions - Data Export management scheduling AP Ready-to-use Report Builder and JavaScript components for charting libraries (Highcharts, BizCharts, Chart.js, etc.) makes it easy to embed data-rich functionality into your products. And you will not have to make custom report queries anymore!
    Starting Price: $349 per month
  • 2
    K2View

    K2View

    K2View

    At K2View, we believe that every enterprise should be able to leverage its data to become as disruptive and agile as the best companies in its industry. We make this possible through our patented Data Product Platform, which creates and manages a complete and compliant dataset for every business entity – on demand, and in real time. The dataset is always in sync with its underlying sources, adapts to changes in the source structures, and is instantly accessible to any authorized data consumer. Data Product Platform fuels many operational use cases, including customer 360, data masking and tokenization, test data management, data migration, legacy application modernization, data pipelining and more – to deliver business outcomes in less than half the time, and at half the cost, of any other alternative. The platform inherently supports modern data architectures – data mesh, data fabric, and data hub – and deploys in cloud, on-premise, or hybrid environments.
  • 3
    Nexla

    Nexla

    Nexla

    Nexla, with its automated approach to data engineering, has for the first time made it possible for data users to get ready-to-use data from any system without any need for connectors or code. Nexla uniquely combines no-code, low-code, and a developer SDK to bring together users across skill levels on to a single platform. With its data-as-a-product core, Nexla combines integration, preparation, monitoring, and delivery of data into a single system regardless of data velocity and format. Today Nexla powers mission critical data for JPMorgan, Doordash, LinkedIn, LiveRamp, J&J, and other leading enterprises across industries.
    Starting Price: $1000/month
  • 4
    Qrvey

    Qrvey

    Qrvey

    Qrvey is the only solution for embedded analytics with a built-in data lake. Qrvey saves engineering teams time and money with a turnkey solution connecting your data warehouse to your SaaS application. Qrvey’s full-stack solution includes the necessary components so that your engineering team can build less. Qrvey’s multi-tenant data lake includes: - Elasticsearch as the analytics engine - A unified data pipeline for ingestion and transformation - A complete semantic layer for simple user and data security integration Qrvey’s embedded visualizations support everything from: - standard dashboards and templates - self-service reporting - user-level personalization - individual dataset creation - data-driven workflow automation Qrvey delivers this as a self-hosted package for cloud environments. This offers the best security as your data never leaves your environment while offering a better analytics experience to users. Less time and money on analytics
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