Compare the Top Data Engineering Tools in India as of October 2026

What are Data Engineering Tools in India?

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 Data Engineering tools in India 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
    Domo

    Domo

    Domo

    Domo’s AI and data platform business is now part of Progress Software. Domo's cloud-native AI data readiness platform complements and significantly broadens Progress' data platform offerings, creating powerful synergies to deliver innovative, secure and scalable AI data readiness solutions worldwide. Together, these capabilities will help customers turn fragmented enterprise data and knowledge into governed, AI-ready intelligence, improving the security, governance and cost of AI-powered initiatives. Domo is the agentic platform for the intelligent enterprise, helping organizations connect, govern, activate, and distribute data and AI. Domo works with cloud data platforms including Snowflake, BigQuery, and Databricks to turn governed data into AI agents, apps, workflows, dashboards, and analytics. Its data foundation, activation, and distribution layers help teams build and deliver intelligence where work happens, with governance, security, and access controls across data and AI.
  • 3
    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.
  • 4
    Nexla

    Nexla

    Nexla

    Nexla is an enterprise-grade, AI-powered data integration platform that unlocks data from any source and transforms it into production-ready data products for AI and agents. With support for 700+ connectors and multiple integration styles, including ELT, ETL, streaming, APIs, and agentic RAG, Nexla enables teams to build and manage data flows without writing code. Innovators like Autodesk, DoorDash, Johnson & Johnson, LinkedIn, and LiveRamp rely on Nexla to ensure mission-critical data flows seamlessly across the enterprise. Nexla processes over one trillion records per month for leading organizations across industries and is recognized in over 14 Gartner 2025 Hype Cycles for Cloud and AI. Rated 4.9/5 on Gartner Peer Insights™, Nexla delivers reliable, scalable, AI-ready data integration. Try Express, the AI Data Engineering Agent for Building Data Pipelines, Express.dev -->
    Starting Price: $50/month
  • 5
    Fivetran

    Fivetran

    Fivetran

    Fivetran is a leading data integration platform that centralizes an organization’s data from various sources to enable modern data infrastructure and drive innovation. It offers over 700 fully managed connectors to move data automatically, reliably, and securely from SaaS applications, databases, ERPs, and files to data warehouses and lakes. The platform supports real-time data syncs and scalable pipelines that fit evolving business needs. Trusted by global enterprises like Dropbox, JetBlue, and Pfizer, Fivetran helps accelerate analytics, AI workflows, and cloud migrations. It features robust security certifications including SOC 1 & 2, GDPR, HIPAA, and ISO 27001. Fivetran provides an easy-to-use, customizable platform that reduces engineering time and enables faster insights.
  • 6
    Kestra

    Kestra

    Kestra

    Kestra is an open-source, event-driven orchestrator that simplifies data operations and improves collaboration between engineers and business users. By bringing Infrastructure as Code best practices to data pipelines, Kestra allows you to build reliable workflows and manage them with confidence. Thanks to the declarative YAML interface for defining orchestration logic, everyone who benefits from analytics can participate in the data pipeline creation process. The UI automatically adjusts the YAML definition any time you make changes to a workflow from the UI or via an API call. Therefore, the orchestration logic is defined declaratively in code, even if some workflow components are modified in other ways.
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