Best Free Data Engineering Tools of 2025

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 application developers and data engineers to access the data from any source in a streamlined manner. - The single schema-less Data API endpoint - Review, configure metrics and dimensions in one place via UI - Data model visualization to make faster decisions - Data Export management scheduling API Our proxy perfectly fits into your current API management ecosystem (versioning, data access, discovery) no matter if you are using Mulesoft, Apigee, Tyk, or your homegrown solution. Leverage the capabilities of Data API and enrich your products with self-service analytics for dashboards, data Exports, or custom report composer for ad-hoc metric querying. Ready-to-use Report Builder and JavaScript components for popular charting libraries (Highcharts, BizCharts, Chart.js, etc.) makes it easy to embed data-rich functionality into your products. Your product or service users will love that because everybody likes to make data-driven decisions! And you will not have to make custom report queries anymore!

ANSI SQL allows you to analyze petabytes worth of data at lightning-fast speeds with no operational overhead. Analytics at scale with 26%-34% less three-year TCO than cloud-based data warehouse alternatives. You can unleash your insights with a trusted platform that is more secure and scales with you. Multi-cloud analytics solutions that allow you to gain insights from all types of data. You can query streaming data in real-time and get the most current information about all your business processes. Machine learning is built-in and allows you to predict business outcomes quickly without having to move data. With just a few clicks, you can securely access and share the analytical insights within your organization. Easy creation of stunning dashboards and reports using popular business intelligence tools right out of the box. BigQuery's strong security, governance, and reliability controls ensure high availability and a 99.9% uptime SLA. Encrypt your data by default and with customer-managed encryption keys

Data engineers and scientists can be 95% better at their jobs with ready access to the most flexible semantic layer, explainable AI and reusable data modelling. They can create and expand semantic models, understand data interrelationships, and run federated query to speed up time to insight. Stardog's graph data virtualization and high performance graph database are the best available -- at a price that is up to 57x less than competitors -- to connect any data source, warehouse, or enterprise data lakehouse without copying or moving data. Scale users and use cases at a lower infrastructure cost. Stardog's intelligent inference engine applies expert knowledge dynamically at query times to uncover hidden patterns and unexpected insights in relationships that lead to better data-informed business decisions and outcomes.

ClearML is an open-source MLOps platform that enables data scientists, ML engineers, and DevOps to easily create, orchestrate and automate ML processes at scale. Our frictionless and unified end-to-end MLOps Suite allows users and customers to concentrate on developing ML code and automating their workflows. ClearML is used to develop a highly reproducible process for end-to-end AI models lifecycles by more than 1,300 enterprises, from product feature discovery to model deployment and production monitoring. You can use all of our modules to create a complete ecosystem, or you can plug in your existing tools and start using them. ClearML is trusted worldwide by more than 150,000 Data Scientists, Data Engineers and ML Engineers at Fortune 500 companies, enterprises and innovative start-ups.

RudderStack is the smart customer information pipeline. You can easily build pipelines that connect your entire customer data stack. Then, make them smarter by pulling data from your data warehouse to trigger enrichment in customer tools for identity sewing and other advanced uses cases. Start building smarter customer data pipelines today.

Dataplane's goal is to make it faster and easier to create a data mesh. It has robust data pipelines and automated workflows that can be used by businesses and teams of any size. Dataplane is more user-friendly and places a greater emphasis on performance, security, resilience, and scaling.

DQOps is a data quality monitoring platform for data teams that helps detect and address quality issues before they impact your business. Track data quality KPIs on data quality dashboards and reach a 100% data quality score. DQOps helps monitor data warehouses and data lakes on the most popular data platforms. DQOps offers a built-in list of predefined data quality checks verifying key data quality dimensions. The extensibility of the platform allows you to modify existing checks or add custom, business-specific checks as needed. The DQOps platform easily integrates with DevOps environments and allows data quality definitions to be stored in a source repository along with the data pipeline code.

Decube is a comprehensive data management platform designed to help organizations manage their data observability, data catalog, and data governance needs. Our platform is designed to provide accurate, reliable, and timely data, enabling organizations to make better-informed decisions. Our data observability tools provide end-to-end visibility into data, making it easier for organizations to track data origin and flow across different systems and departments. With our real-time monitoring capabilities, organizations can detect data incidents quickly and reduce their impact on business operations. The data catalog component of our platform provides a centralized repository for all data assets, making it easier for organizations to manage and govern data usage and access. With our data classification tools, organizations can identify and manage sensitive data more effectively, ensuring compliance with data privacy regulations and policies. The data governance component of our platform provides robust access controls, enabling organizations to manage data access and usage effectively. Our tools also allow organizations to generate audit reports, track user activity, and demonstrate compliance with regulatory requirements.

Answer questions today, not next week. Latitude makes it easy to create low-code data apps within minutes. You don't need a data stack, but you can help your team answer data-related questions. Connect your data sources to Latitude and you can immediately start exploring your data. Latitude connects with your database, data warehouse, or other tools used by your team. Multiple sources can be used in the same analysis. We support over 100 data sources. Latitude offers a vast array of data sources that can be used by teams to explore and transform data. This includes using our AI SQL Assistant, visual programming, and manually writing SQL queries. Latitude combines data exploration with visualization. You can choose from tables or charts and add them to the canvas you are currently working on. Interactive views are easy to create because your canvas already knows how variables and transformations work together.

Prophecy allows you to connect with many more people, including data analysts and visual ETL developers. To create your pipelines, all you have to do is click and type a few SQL expressions. You will be creating high-quality, readable code for Spark or Airflow by using the Low-Code Designer. This code is then committed to your Git. Prophecy provides a gem builder that allows you to quickly create and roll out your own Frameworks. Data Quality, Encryption and new Sources are just a few examples. Prophecy offers best practices and infrastructure as managed service - making your life and operations easier! Prophecy makes it easy to create workflows that are high-performance and scale out using the cloud.

No more low-level code or gluing together complex systems. SQL makes it easy to build and deploy pipelines quickly. Data engineering service that allows developers and data engineers to quickly build and deploy data pipelines for data-driven apps. It is easy to connect to and find available data using pre-built connectors for messaging, storage, and database engines. Each connection you make will result in a stream of data to or from the system. You can create your pipelines using SQL with Decodable. Pipelines use streams to send and receive data to and from your connections. Streams can be used to connect pipelines to perform the most difficult processing tasks. To ensure data flows smoothly, monitor your pipelines. Create curated streams that can be used by other teams. To prevent data loss due to system failures, you should establish retention policies for streams. You can monitor real-time performance and health metrics to see if everything is working.

DataLakeHouse.io Data Sync allows users to replicate and synchronize data from operational systems (on-premises and cloud-based SaaS), into destinations of their choice, primarily Cloud Data Warehouses. DLH.io is a tool for marketing teams, but also for any data team in any size organization. It enables business cases to build single source of truth data repositories such as dimensional warehouses, data vaults 2.0, and machine learning workloads. Use cases include technical and functional examples, including: ELT and ETL, Data Warehouses, Pipelines, Analytics, AI & Machine Learning and Data, Marketing and Sales, Retail and FinTech, Restaurants, Manufacturing, Public Sector and more. DataLakeHouse.io has a mission: to orchestrate the data of every organization, especially those who wish to become data-driven or continue their data-driven strategy journey. DataLakeHouse.io, aka DLH.io, allows hundreds of companies manage their cloud data warehousing solutions.

Data engineering workflows that are powerful, but without the headaches of infrastructure. Simple, reusable Python is used to define complex streaming, scheduling and data backfill pipelines. Fetch all your data in real time, no matter how complicated. Deep learning and LLMs can be used to make decisions along with structured business data. Don't pay vendors for data that you won't use. Instead, query data right before online predictions. Experiment with Jupyter and then deploy into production. Create new data workflows and prevent train-serve skew in milliseconds. Instantly monitor your data workflows and track usage and data quality. You can see everything you have computed, and the data will replay any information. Integrate with your existing tools and deploy it to your own infrastructure. Custom hold times and withdrawal limits can be set.

DatErica: Revolutionizing Data Processing DatErica, a cutting edge data processing platform, automates and streamlines data operations. It provides scalable, flexible solutions to complex data requirements by leveraging a robust technology stack that includes Node.js. The platform provides advanced ETL capabilities and seamless data integration across multiple sources. It also offers secure data warehousing. DatErica’s AI-powered tools allow sophisticated data transformation and verification, ensuring accuracy. Users can make informed decisions with real-time analytics and customizable dashboards. The user-friendly interface simplifies the workflow management while real-time monitoring, alerts and notifications enhance operational efficiency. DatErica is perfect for data engineers, IT teams and businesses that want to optimize their data processes.

The Databricks Data Intelligence Platform enables your entire organization to utilize data and AI. It is built on a lakehouse that provides an open, unified platform for all data and governance. It's powered by a Data Intelligence Engine, which understands the uniqueness in your data. Data and AI companies will win in every industry. Databricks can help you achieve your data and AI goals faster and easier. Databricks combines the benefits of a lakehouse with generative AI to power a Data Intelligence Engine which understands the unique semantics in your data. The Databricks Platform can then optimize performance and manage infrastructure according to the unique needs of your business. The Data Intelligence Engine speaks your organization's native language, making it easy to search for and discover new data. It is just like asking a colleague a question.

AI teams are faced with challenges that require new technologies. These technologies are built by us. Existing data lakes and data warehouses do not work with unstructured data like text, images, or videos. AI and software development go hand in hand. Built with data scientists, ML experts, and data engineers at heart. Don't reinvent your wheel! Production is fast and cost-effective. All your data is stored by you. Your machines are used to train your models. Existing data lakes and data warehouses do not work with unstructured data like text, images, or videos. New technologies are required for AI teams. These technologies are built by us. Studio is an extension to BitBucket, GitLab, and GitHub. Register for the online SaaS version, or contact us to start an on-premise installation

Bodo's powerful parallel computing engine and powerful compute engine provide efficient execution and effective scaling, even for 10,000+ cores or PBs of data. Bodo makes it easier to develop and maintain data science, data engineering, and ML workloads using standard Python APIs such as Pandas. End-to-end compilation prevents frequent failures and catches errors before they reach production. With Python's simplicity, you can experiment faster with large datasets from your laptop. Produce production-ready code without having to refactor for scaling large infrastructure.

You can instantly see the order in your complex data world and know exactly where to find answers. Datakin automatically tracks data lineage and displays your entire data ecosystem as a rich visual graph. It clearly shows the upstream and downstream relationships of each dataset. The Duration tab summarizes the job's performance and its upstream dependencies in a Gantt-style graph. This makes it easy to identify bottlenecks. The Compare tab allows you to see how your jobs and data have changed over time. Sometimes jobs that run well can produce poor output. The Quality tab shows you the most important data quality metrics and how they change over time. This makes anomalies easily visible. Datakin allows you to quickly identify the root cause of problems and prevent them from happening again.

Kestra is a free, open-source orchestrator based on events that simplifies data operations while improving collaboration between engineers and users. Kestra brings Infrastructure as Code to data pipelines. This allows you to build reliable workflows with confidence. The declarative YAML interface allows anyone who wants to benefit from analytics to participate in the creation of the data pipeline. The UI automatically updates the YAML definition whenever you make changes to a work flow via the UI or an API call. The orchestration logic can be defined in code declaratively, even if certain workflow components are modified.

Ask On Data is an open source Data Engineering/ ETL software that uses chat-based AI. Ask On Data, with its agentic capabilities and next-gen data stack pioneering technology, can help create data pipelines through a simple chat interface. It can be used to perform tasks such as Data Migration, Data Loading and Data Transformations. It also allows for Data Cleaning, Data Wrangling and Data Analysis. Data Scientists can use this tool to get clean data. Data Analysts and BI Engineers can create calculated tables. Data Engineers will also be able to use this tool in order to increase their efficiency.