Best Free Data Pipeline Software of 2026 - Page 2

Data integration, backup, management and connectivity. Cloud-based platform that is 100 percent cloud-based. It offers cloud agility and scalability. No manual upgrades or deployment required. There is no coding wizard that can meet the needs of both IT professionals as well as business users without technical skills. Skyvia suites are available in flexible pricing plans that can be customized for any product. To automate workflows, connect your cloud, flat, and on-premise data. Automate data collection from different cloud sources to a database. In just a few clicks, you can transfer your business data between cloud applications. All your cloud data can be protected and kept secure in one location. To connect with multiple OData consumers, you can share data instantly via the REST API. You can query and manage any data via the browser using SQL or the intuitive visual Query Builder.

QVIKPREP's Data Prep Runner (DPR) revolutionizes the process of preparing data and enhances data management efficiency. By streamlining data processing, businesses can refine their operations, effortlessly compare datasets, and improve data profiling. This tool helps save valuable time when preparing data for tasks such as operational reporting, data analysis, and transferring data across various systems. Additionally, it minimizes risks associated with data integration project timelines, allowing teams to identify potential issues early through effective data profiling. Automation of data processing further boosts productivity for operations teams, while the easy management of data prep enables the creation of a resilient data pipeline. DPR employs historical data checks to enhance accuracy, ensuring that transactions are efficiently directed into systems and that data is leveraged for automated testing. By guaranteeing timely delivery of data integration projects, it allows organizations to identify and resolve data issues proactively, rather than during testing phases. The tool also facilitates data validation through established rules and enables the correction of data within the pipeline. With its color-coded reports, DPR simplifies the process of comparing data from different sources, making it a vital asset for any organization. Ultimately, leveraging DPR not only enhances operational efficiency but also fosters a culture of data-driven decision-making.

Data-driven computational pipelines. Nextflow allows for reproducible and scalable scientific workflows by using software containers. It allows adaptation of scripts written in most common scripting languages. Fluent DSL makes it easy to implement and deploy complex reactive and parallel workflows on clusters and clouds. Nextflow was built on the belief that Linux is the lingua Franca of data science. Nextflow makes it easier to create a computational pipeline that can be used to combine many tasks. You can reuse existing scripts and tools. Additionally, you don't have to learn a new language to use Nextflow. Nextflow supports Docker, Singularity and other containers technology. This, together with integration of the GitHub Code-sharing Platform, allows you write self-contained pipes, manage versions, reproduce any configuration quickly, and allow you to integrate the GitHub code-sharing portal. Nextflow acts as an abstraction layer between the logic of your pipeline and its execution layer.

Experience robust data engineering processes free from the challenges of infrastructure management. By utilizing straightforward, modular Python, you can define intricate streaming, scheduling, and data backfill pipelines with ease. Transition from traditional ETL methods and access your data instantly, regardless of its complexity. Seamlessly blend deep learning and large language models with structured business datasets to enhance decision-making. Improve forecasting accuracy using up-to-date information, eliminate the costs associated with vendor data pre-fetching, and conduct timely queries for online predictions. Test your ideas in Jupyter notebooks before moving them to a live environment. Avoid discrepancies between training and serving data while developing new workflows in mere milliseconds. Monitor all of your data operations in real-time to effortlessly track usage and maintain data integrity. Have full visibility into everything you've processed and the ability to replay data as needed. Easily integrate with existing tools and deploy on your infrastructure, while setting and enforcing withdrawal limits with tailored hold periods. With such capabilities, you can not only enhance productivity but also ensure streamlined operations across your data ecosystem.

Ask On Data is an innovative, chat-based open source tool designed for Data Engineering and ETL processes, equipped with advanced agentic capabilities and a next-generation data stack. It simplifies the creation of data pipelines through an intuitive chat interface. Users can perform a variety of tasks such as Data Migration, Data Loading, Data Transformations, Data Wrangling, Data Cleaning, and even Data Analysis effortlessly through conversation. This versatile tool is particularly beneficial for Data Scientists seeking clean datasets, while Data Analysts and BI engineers can utilize it to generate calculated tables. Additionally, Data Engineers can enhance their productivity and accomplish significantly more with this efficient solution. Ultimately, Ask On Data streamlines data management tasks, making it an invaluable resource in the data ecosystem.

The Databricks Data Intelligence Platform empowers every member of your organization to leverage data and artificial intelligence effectively. Constructed on a lakehouse architecture, it establishes a cohesive and transparent foundation for all aspects of data management and governance, enhanced by a Data Intelligence Engine that recognizes the distinct characteristics of your data. Companies that excel across various sectors will be those that harness the power of data and AI. Covering everything from ETL processes to data warehousing and generative AI, Databricks facilitates the streamlining and acceleration of your data and AI objectives. By merging generative AI with the integrative advantages of a lakehouse, Databricks fuels a Data Intelligence Engine that comprehends the specific semantics of your data. This functionality enables the platform to optimize performance automatically and manage infrastructure in a manner tailored to your organization's needs. Additionally, the Data Intelligence Engine is designed to grasp the unique language of your enterprise, making the search and exploration of new data as straightforward as posing a question to a colleague, thus fostering collaboration and efficiency. Ultimately, this innovative approach transforms the way organizations interact with their data, driving better decision-making and insights.

Upsolver makes it easy to create a governed data lake, manage, integrate, and prepare streaming data for analysis. Only use auto-generated schema on-read SQL to create pipelines. A visual IDE that makes it easy to build pipelines. Add Upserts to data lake tables. Mix streaming and large-scale batch data. Automated schema evolution and reprocessing of previous state. Automated orchestration of pipelines (no Dags). Fully-managed execution at scale Strong consistency guarantee over object storage Nearly zero maintenance overhead for analytics-ready information. Integral hygiene for data lake tables, including columnar formats, partitioning and compaction, as well as vacuuming. Low cost, 100,000 events per second (billions every day) Continuous lock-free compaction to eliminate the "small file" problem. Parquet-based tables are ideal for quick queries.

Montara enables BI Teams and Data Analysts to model and transform data using SQL alone, easily and seamlessly, and enjoy benefits such a modular code, CI/CD and versioning, automated testing and documentation. With Montara, analysts are able to quickly understand the impact of changes in models on analysis, reports, and dashboards. Report-level lineage is supported, as well as support for 3rd-party visualization tools like Tableau and Looker. BI teams can also perform ad hoc analysis, create dashboards and reports directly on Montara.

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.