Best Data Pipeline Software with a Free Trial of 2025 - Page 2

GlassFlow is an innovative, serverless platform for building event-driven data pipelines, specifically tailored for developers working with Python. It allows users to create real-time data workflows without the complexities associated with traditional infrastructure solutions like Kafka or Flink. Developers can simply write Python functions to specify data transformations, while GlassFlow takes care of the infrastructure, providing benefits such as automatic scaling, low latency, and efficient data retention. The platform seamlessly integrates with a variety of data sources and destinations, including Google Pub/Sub, AWS Kinesis, and OpenAI, utilizing its Python SDK and managed connectors. With a low-code interface, users can rapidly set up and deploy their data pipelines in a matter of minutes. Additionally, GlassFlow includes functionalities such as serverless function execution, real-time API connections, as well as alerting and reprocessing features. This combination of capabilities makes GlassFlow an ideal choice for Python developers looking to streamline the development and management of event-driven data pipelines, ultimately enhancing their productivity and efficiency. As the data landscape continues to evolve, GlassFlow positions itself as a pivotal tool in simplifying data processing workflows.

Effortlessly manage, process, and transform CAD, FE, CFD, and test data with ease. Establish automatic data pipelines for machine learning, reduced order modeling, and 3D deep learning applications. Eliminate the complexity of data science without the need for coding. Key Ward's platform stands out as the pioneering end-to-end no-code engineering solution, fundamentally changing the way engineers work with their data, whether it be experimental or CAx. By harnessing the power of engineering data intelligence, our software empowers engineers to seamlessly navigate their multi-source data, extracting immediate value through integrated advanced analytics tools while also allowing for the custom development of machine learning and deep learning models, all within a single platform with just a few clicks. Centralize, update, extract, sort, clean, and prepare your diverse data sources for thorough analysis, machine learning, or deep learning applications automatically. Additionally, leverage our sophisticated analytics tools on your experimental and simulation data to uncover correlations, discover dependencies, and reveal underlying patterns that can drive innovation in engineering processes. Ultimately, this approach streamlines workflows, enhancing productivity and enabling more informed decision-making in engineering endeavors.

Streamkap is a modern streaming ETL platform built on top of Apache Kafka and Flink, designed to replace batch ETL with streaming in minutes. It enables data movement with sub-second latency using change data capture for minimal impact on source databases and real-time updates. The platform offers dozens of pre-built, no-code source connectors, automated schema drift handling, updates, data normalization, and high-performance CDC for efficient and low-impact data movement. Streaming transformations power faster, cheaper, and richer data pipelines, supporting Python and SQL transformations for common use cases like hashing, masking, aggregations, joins, and unnesting JSON. Streamkap allows users to connect data sources and move data to target destinations with an automated, reliable, and scalable data movement platform. It supports a broad range of event and database sources.

DocumentsPipeliner serves as a middleware solution hosted on a server, designed for the automated handling of incoming documents. It actively monitors various input channels, such as mailboxes (like Microsoft Exchange) and file directories, extracting email attachments, standardizing formats (for instance, PDF/A), and enhancing documents with relevant metadata from external systems when required. Subsequently, it transmits the processed information to designated systems, including M-Files, ABBYY FlexiCapture, or other document management and workflow solutions, according to established rules. By using DocumentsPipeliner, organizations can establish a centralized “digital mailroom” that streamlines routine document processing, ensures adherence to compliance standards, and establishes a robust foundation for consistent and scalable operational processes. This innovative approach not only enhances efficiency but also allows companies to better manage their document workflows.

Etleap was created on AWS to support Redshift, snowflake and S3/Glue data warehouses and data lakes. Their solution simplifies and automates ETL through fully-managed ETL as-a-service. Etleap's data wrangler allows users to control how data is transformed for analysis without having to write any code. Etleap monitors and maintains data pipes for availability and completeness. This eliminates the need for constant maintenance and centralizes data sourced from 50+ sources and silos into your database warehouse or data lake.

Alooma provides data teams with the ability to monitor and manage their data effectively. It consolidates information from disparate data silos into BigQuery instantly, allowing for real-time data integration. Users can set up data flows in just a few minutes, or opt to customize, enhance, and transform their data on-the-fly prior to it reaching the data warehouse. With Alooma, no event is ever lost thanks to its integrated safety features that facilitate straightforward error management without interrupting the pipeline. Whether dealing with a few data sources or a multitude, Alooma's flexible architecture adapts to meet your requirements seamlessly. This capability ensures that organizations can efficiently handle their data demands regardless of scale or complexity.

Fivetran is a comprehensive data integration solution designed to centralize and streamline data movement for organizations of all sizes. With more than 700 pre-built connectors, it effortlessly transfers data from SaaS apps, databases, ERPs, and files into data warehouses and lakes, enabling real-time analytics and AI-driven insights. The platform’s scalable pipelines automatically adapt to growing data volumes and business complexity. Leading companies such as Dropbox, JetBlue, Pfizer, and National Australia Bank rely on Fivetran to reduce data ingestion time from weeks to minutes and improve operational efficiency. Fivetran offers strong security compliance with certifications including SOC 1 & 2, GDPR, HIPAA, ISO 27001, PCI DSS, and HITRUST. Users can programmatically create and manage pipelines through its REST API for seamless extensibility. The platform supports governance features like role-based access controls and integrates with transformation tools like dbt Labs. Fivetran helps organizations innovate by providing reliable, secure, and automated data pipelines tailored to their evolving needs.

Open core technology facilitates the integration of hybrid and multi-cloud environments. Built on the open-source initiative CDAP, Data Fusion guarantees portability of data pipelines for its users. The extensive compatibility of CDAP with both on-premises and public cloud services enables Cloud Data Fusion users to eliminate data silos and access previously unreachable insights. Additionally, its seamless integration with Google’s top-tier big data tools enhances the user experience. By leveraging Google Cloud, Data Fusion not only streamlines data security but also ensures that data is readily available for thorough analysis. Whether you are constructing a data lake utilizing Cloud Storage and Dataproc, transferring data into BigQuery for robust data warehousing, or transforming data for placement into a relational database like Cloud Spanner, the integration capabilities of Cloud Data Fusion promote swift and efficient development while allowing for rapid iteration. This comprehensive approach ultimately empowers businesses to derive greater value from their data assets.

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.

If you're looking to establish a governed delta lake, create a data warehouse, or transition from a conventional database to a contemporary cloud data solution, Lyftrondata has you covered. You can effortlessly create and oversee all your data workloads within a single platform, automating the construction of your pipeline and warehouse. Instantly analyze your data using ANSI SQL and business intelligence or machine learning tools, and easily share your findings without the need for custom coding. This functionality enhances the efficiency of your data teams and accelerates the realization of value. You can define, categorize, and locate all data sets in one centralized location, enabling seamless sharing with peers without the complexity of coding, thus fostering insightful data-driven decisions. This capability is particularly advantageous for organizations wishing to store their data once, share it with various experts, and leverage it repeatedly for both current and future needs. In addition, you can define datasets, execute SQL transformations, or migrate your existing SQL data processing workflows to any cloud data warehouse of your choice, ensuring flexibility and scalability in your data management strategy.

Gravity aims to simplify the process of streaming data from over 100 different sources, allowing users to pay only for what they actually utilize. By providing a straightforward interface, Gravity eliminates the need for engineering teams to create streaming pipelines, enabling users to set up streaming from databases, event data, and APIs in just minutes. This empowers everyone on the data team to engage in a user-friendly point-and-click environment, allowing you to concentrate on developing applications, services, and enhancing customer experiences. Additionally, Gravity offers comprehensive execution tracing and detailed error messages for swift problem identification and resolution. To facilitate a quick start, we have introduced various new features, including bulk setup options, predefined schemas, data selection capabilities, and numerous job modes and statuses. With Gravity, you can spend less time managing infrastructure and more time performing data analysis, as our intelligent engine ensures your pipelines run seamlessly. Furthermore, Gravity provides integration with your existing systems for effective notifications and orchestration, enhancing overall workflow efficiency. Ultimately, Gravity equips your team with the tools needed to transform data into actionable insights effortlessly.

Create a scalable architecture that treats data products as first-class citizens. Automate and repurpose data products. Enable compliance and robust data governance. Control the costs of your data products and pipelines for Snowflake. This global pharmaceutical giant's data product teams can benefit from next-generation analytics using self-service data and analytics infrastructure that includes Snowflake and other tools that use a data mesh approach. The DataOps.live platform allows them to organize and benefit from next generation analytics. DataOps is a unique way for development teams to work together around data in order to achieve rapid results and improve customer service. Data warehousing has never been paired with agility. DataOps is able to change all of this. Governance of data assets is crucial, but it can be a barrier to agility. Dataops enables agility and increases governance. DataOps does not refer to technology; it is a way of thinking.

Talend Pipeline Designer is an intuitive web-based application designed for users to transform raw data into a format suitable for analytics. It allows for the creation of reusable pipelines that can extract, enhance, and modify data from various sources before sending it to selected data warehouses, which can then be used to generate insightful dashboards for your organization. With this tool, you can efficiently build and implement data pipelines in a short amount of time. The user-friendly visual interface enables both design and preview capabilities for batch or streaming processes directly within your web browser. Its architecture is built to scale, supporting the latest advancements in hybrid and multi-cloud environments, while enhancing productivity through real-time development and debugging features. The live preview functionality provides immediate visual feedback, allowing you to diagnose data issues swiftly. Furthermore, you can accelerate decision-making through comprehensive dataset documentation, quality assurance measures, and effective promotion strategies. The platform also includes built-in functions to enhance data quality and streamline the transformation process, making data management an effortless and automated practice. In this way, Talend Pipeline Designer empowers organizations to maintain high data integrity with ease.

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.

Orchestra serves as a Comprehensive Control Platform for Data and AI Operations, aimed at empowering data teams to effortlessly create, deploy, and oversee workflows. This platform provides a declarative approach that merges coding with a graphical interface, enabling users to develop workflows at a tenfold speed while cutting maintenance efforts by half. Through its real-time metadata aggregation capabilities, Orchestra ensures complete data observability, facilitating proactive alerts and swift recovery from any pipeline issues. It smoothly integrates with a variety of tools such as dbt Core, dbt Cloud, Coalesce, Airbyte, Fivetran, Snowflake, BigQuery, Databricks, and others, ensuring it fits well within existing data infrastructures. With a modular design that accommodates AWS, Azure, and GCP, Orchestra proves to be a flexible option for businesses and growing organizations looking to optimize their data processes and foster confidence in their AI ventures. Additionally, its user-friendly interface and robust connectivity options make it an essential asset for organizations striving to harness the full potential of their data ecosystems.

Connect and centralize data. Transform your data landscape into a flexible powerhouse. Data Virtuality is a data integration platform that allows for instant data access, data centralization, and data governance. Logical Data Warehouse combines materialization and virtualization to provide the best performance. For high data quality, governance, and speed-to-market, create your single source data truth by adding a virtual layer to your existing data environment. Hosted on-premises or in the cloud. Data Virtuality offers three modules: Pipes Professional, Pipes Professional, or Logical Data Warehouse. You can cut down on development time up to 80% Access any data in seconds and automate data workflows with SQL. Rapid BI Prototyping allows for a significantly faster time to market. Data quality is essential for consistent, accurate, and complete data. Metadata repositories can be used to improve master data management.

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.

Ingestro, formerly known as nuvo, delivers a powerful AI-driven platform that modernizes the entire customer data import process for SaaS companies. Its technology automatically organizes, validates, and converts messy spreadsheets and multi-format files into structured data that matches each product’s unique model. Teams can use the no-code importer, the customizable SDK, or advanced Data Pipelines to integrate fast, accurate, and scalable imports directly into their applications. Designed to reduce manual cleanup, Ingestro’s smart mapping and validation rules catch errors early and eliminate the need for tedious reformatting. The system handles billions of rows, supports 50+ languages, and prioritizes security with ISO certifications and strict compliance standards. With guided onboarding, pre-built sandboxes, and AI-assisted setup, companies can deploy a production-ready importer in minimal time. Leading businesses report significant gains in productivity and customer onboarding efficiency after adopting Ingestro. The platform ultimately helps product, engineering, and CS teams deliver cleaner data, faster implementation, and a superior user experience.

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.

Unravel empowers data functionality across various environments, whether it’s Azure, AWS, GCP, or your own data center, by enhancing performance, automating issue resolution, and managing expenses effectively. It enables users to oversee, control, and optimize their data pipelines both in the cloud and on-site, facilitating a more consistent performance in the applications that drive business success. With Unravel, you gain a holistic perspective of your complete data ecosystem. The platform aggregates performance metrics from all systems, applications, and platforms across any cloud, employing agentless solutions and machine learning to thoroughly model your data flows from start to finish. This allows for an in-depth exploration, correlation, and analysis of every component within your contemporary data and cloud infrastructure. Unravel's intelligent data model uncovers interdependencies, identifies challenges, and highlights potential improvements, providing insight into how applications and resources are utilized, as well as distinguishing between effective and ineffective elements. Instead of merely tracking performance, you can swiftly identify problems and implement solutions. Utilize AI-enhanced suggestions to automate enhancements, reduce expenses, and strategically prepare for future needs. Ultimately, Unravel not only optimizes your data management strategies but also supports a proactive approach to data-driven decision-making.

CData Sync is a universal database pipeline that automates continuous replication between hundreds SaaS applications & cloud-based data sources. It also supports any major data warehouse or database, whether it's on-premise or cloud. Replicate data from hundreds cloud data sources to popular databases destinations such as SQL Server and Redshift, S3, Snowflake and BigQuery. It is simple to set up replication: log in, select the data tables you wish to replicate, then select a replication period. It's done. CData Sync extracts data iteratively. It has minimal impact on operational systems. CData Sync only queries and updates data that has been updated or added since the last update. CData Sync allows for maximum flexibility in partial and full replication scenarios. It ensures that critical data is safely stored in your database of choice. Get a 30-day trial of the Sync app for free or request more information at www.cdata.com/sync