Best Data Pipeline Software - Page 4
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Compare the Top Data Pipeline Software as of November 2026 - Page 4
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1
Meltano
Meltano
Meltano provides the ultimate flexibility in deployment options. Own your data stack, end to end. Ever growing connector library of 300+ connectors have been running in production for years. Run workflows in isolated environments, execute end-to-end tests, and version control everything. Open source gives you the power to build your ideal data stack. Define your entire project as code and collaborate confidently with your team. The Meltano CLI enables you to rapidly create your project, making it easy to start replicating data. Meltano is designed to be the best way to run dbt to manage your transformations. Your entire data stack is defined in your project, making it simple to deploy it to production. Validate your changes in development before moving to CI, and in staging before moving to production. -
2
Azkaban
Azkaban
Azkaban is a distributed Workflow Manager, implemented at LinkedIn to solve the problem of Hadoop job dependencies. We had jobs that needed to run in order, from ETL jobs to data analytics products. After version 3.0, we provide two modes: the stand alone “solo-server” mode and distributed multiple-executor mode. The following describes the differences between the two modes. In solo server mode, the DB is embedded H2 and both web server and executor server run in the same process. This should be useful if one just wants to try things out. It can also be used on small scale use cases. The multiple executor mode is for most serious production environment. Its DB should be backed by MySQL instances with master-slave set up. The web server and executor servers should ideally run in different hosts so that upgrading and maintenance shouldn’t affect users. This multiple host setup brings in robust and scalable aspect to Azkaban. -
3
Ingestro
Ingestro
Ingestro is an enterprise-grade, AI-powered data import solution designed to help software companies clean, validate, and onboard customer data faster. It supports uploads from a wide variety of formats—including CSV, Excel, XML, JSON, and even PDFs—while automatically mapping, cleaning, and restructuring the data to match each company’s schema. With its Data Importer SDK and Data Pipelines, Ingestro enables teams to offer a seamless self-serve import experience without building in-house tools. The platform improves scalability by automating recurring data onboarding tasks, reducing dependency on developers, and accelerating customer time-to-value. Companies rely on Ingestro to process billions of records securely thanks to features like ISO 27001 certification, GDPR compliance, and optional self-hosting. By transforming tedious data imports into smooth, AI-enhanced workflows, Ingestro helps product, engineering, and customer success teams reclaim valuable time. -
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datuum.ai
Datuum
AI-powered data integration tool that helps streamline the process of customer data onboarding. It allows for easy and fast automated data integration from various sources without coding, reducing preparation time to just a few minutes. With Datuum, organizations can efficiently extract, ingest, transform, migrate, and establish a single source of truth for their data, while integrating it into their existing data storage. Datuum is a no-code product and can reduce up to 80% of the time spent on data-related tasks, freeing up time for organizations to focus on generating insights and improving the customer experience. With over 40 years of experience in data management and operations, we at Datuum have incorporated our expertise into the core of our product, addressing the key challenges faced by data engineers and managers and ensuring that the platform is user-friendly, even for non-technical specialists. -
5
Montara
Montara
Montara enables BI teams and data analysts, using SQL only, to model and transform their data easily and seamlessly and enjoy benefits such as modular code, CI/CD, versioning and automated testing and documentation. With Montara, analysts can quickly understand how changes to models impact analysis, reports and dashboards with report-level lineage and support for 3rd party visualization tools such as Tableau and Looker. Furthermore, BI teams can perform ad-hoc analysis and create reports and dashboards on Montara directly.Starting Price: $100/user/month -
6
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. -
7
Pantomath
Pantomath
Organizations continuously strive to be more data-driven, building dashboards, analytics, and data pipelines across the modern data stack. Unfortunately, most organizations struggle with data reliability issues leading to poor business decisions and lack of trust in data as an organization, directly impacting their bottom line. Resolving complex data issues is a manual and time-consuming process involving multiple teams all relying on tribal knowledge to manually reverse engineer complex data pipelines across different platforms to identify root-cause and understand the impact. Pantomath is a data pipeline observability and traceability platform for automating data operations. It continuously monitors datasets and jobs across the enterprise data ecosystem providing context to complex data pipelines by creating automated cross-platform technical pipeline lineage. -
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Tarsal
Tarsal
Tarsal's infinite scalability means as your organization grows, Tarsal grows with you. Tarsal makes it easy for you to switch where you're sending data - today's SIEM data is tomorrow's data lake data; all with one click. Keep your SIEM and gradually migrate analytics over to a data lake. You don't have to rip anything out to use Tarsal. Some analytics just won't run on your SIEM. Use Tarsal to have query-ready data on a data lake. Your SIEM is one of the biggest line items in your budget. Use Tarsal to send some of that data to your data lake. Tarsal is the first highly scalable ETL data pipeline built for security teams. Easily exfil terabytes of data in just just a few clicks, with instant normalization, and route that data to your desired destination. -
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definity
definity
Monitor and control everything your data pipelines do with zero code changes. Monitor data and pipelines in motion to proactively prevent downtime and quickly root cause issues. Optimize pipeline runs and job performance to save costs and keep SLAs. Accelerate code deployments and platform upgrades while maintaining reliability and performance. Data & performance checks in line with pipeline runs. Checks on input data, before pipelines even run. Automatic preemption of runs. definity takes away the effort to build deep end-to-end coverage, so you are protected at every step, across every dimension. definity shifts observability to post-production to achieve ubiquity, increase coverage, and reduce manual effort. definity agents automatically run with every pipeline, with zero footprints. Unified view of data, pipelines, infra, lineage, and code for every data asset. Detect in run-time and avoid async checks. Auto-preempt runs, even on inputs. -
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Observo AI
Observo AI
Observo AI is an AI-native data pipeline platform designed to address the challenges of managing vast amounts of telemetry data in security and DevOps operations. By leveraging machine learning and agentic AI, Observo AI automates data optimization, enabling enterprises to process AI-generated data more efficiently, securely, and cost-effectively. It reduces data processing costs by over 50% and accelerates incident response times by more than 40%. Observo AI's features include intelligent data deduplication and compression, real-time anomaly detection, and dynamic data routing to appropriate storage or analysis tools. It also enriches data streams with contextual information to enhance threat detection accuracy while minimizing false positives. Observo AI offers a searchable cloud data lake for efficient data storage and retrieval. -
11
Onum
Onum
Onum is a real-time data intelligence platform that empowers security and IT teams to derive actionable insights from data in-stream, facilitating rapid decision-making and operational efficiency. By processing data at the source, Onum enables decisions in milliseconds, not minutes, simplifying complex workflows and reducing costs. It offers data reduction capabilities, intelligently filtering and reducing data at the source to ensure only valuable information reaches analytics platforms, thereby minimizing storage requirements and associated costs. It also provides data enrichment features, transforming raw data into actionable intelligence by adding context and correlations in real time. Onum simplifies data pipeline management through efficient data routing, ensuring the right data is delivered to the appropriate destinations instantly, supporting various sources and destinations. -
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DataBahn
DataBahn
DataBahn.ai is redefining how enterprises manage the explosion of security and operational data in the AI era. Our AI-powered data pipeline and fabric platform helps organizations securely collect, enrich, orchestrate, and optimize enterprise data—including security, application, observability, and IoT/OT telemetry—for analytics, automation, and AI. With native support for over 400 integrations and built-in enrichment capabilities, DataBahn streamlines fragmented data workflows and reduces SIEM and infrastructure costs from day one. The platform requires no specialist training, enabling security and IT teams to extract insights in real time and adapt quickly to new demands. We've helped Fortune 500 and Global 2000 companies reduce data processing costs by over 50% and automate more than 80% of their data engineering workloads. -
13
Tenzir
Tenzir
Tenzir is a data pipeline engine specifically designed for security teams, facilitating the collection, transformation, enrichment, and routing of security data throughout its lifecycle. It enables users to seamlessly gather data from various sources, parse unstructured data into structured formats, and transform it as needed. It optimizes data volume, reduces costs, and supports mapping to standardized schemas like OCSF, ASIM, and ECS. Tenzir ensures compliance through data anonymization features and enriches data by adding context from threats, assets, and vulnerabilities. It supports real-time detection and stores data efficiently in Parquet format within object storage systems. Users can rapidly search and materialize necessary data and reactivate at-rest data back into motion. Tension is built for flexibility, allowing deployment as code and integration into existing workflows, ultimately aiming to reduce SIEM costs and provide full control. -
14
QuickLaunch Analytics
QuickLaunch Analytics
QuickLaunch Analytics is an enterprise data analytics platform that helps organizations turn fragmented data from ERP, CRM, financial, HR and operational systems into a unified, governed analytics ecosystem with faster, business-ready insights; rather than building analytics infrastructure from scratch, it provides a Foundation Pack that includes automated data pipelines, a cloud-native data lakehouse and Power BI semantic models so raw enterprise data can be integrated, cleaned, and governed for analytics, and Application Packs that layer pre-built, application-specific intelligence and production-ready semantic models tailored to systems like JD Edwards, Viewpoint Vista, NetSuite, Salesforce and others to decode complex data structures into business-friendly metrics and dashboards; the platform accelerates time-to-insight from months/years to weeks with standardized metrics and reports, supports cross-application analysis and self-service BI, and uses modern technologies. -
15
SAS Studio
SAS
SAS Studio provides a web browser-based programming environment, so writing and interacting with SAS code is easier and faster, wherever you are. It helps teams build efficient data pipelines with a data engineering experience designed for seamless collaboration, low-code work, and open source integration. SAS Studio connects to leading cloud data platforms such as AWS Redshift and S3, Google BigQuery and Cloud Storage, and Azure Data Lake Storage, as well as relational and nonrelational databases, including Oracle, Snowflake, Teradata, SingleStore, MongoDB, and other sources. It also works with file formats such as Excel, text, Parquet, and ORC. Users can choose no code, low code, or code by creating end-to-end data pipelines with drag-and-drop steps, developing Python and SAS code assets in SAS Studio or another IDE, and embedding them into SAS Studio flows for secure, centralized access to data sources and governed execution. SAS Studio supports ELT and ETL approaches. -
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Informatica Data Engineering
Informatica
Ingest, prepare, and process data pipelines at scale for AI and analytics in the cloud. Informatica’s comprehensive data engineering portfolio provides everything you need to process and prepare big data engineering workloads to fuel AI and analytics: robust data integration, data quality, streaming, masking, and data preparation capabilities. Rapidly build intelligent data pipelines with CLAIRE®-powered automation, including automatic change data capture (CDC) Ingest thousands of databases and millions of files, and streaming events. Accelerate time-to-value ROI with self-service access to trusted, high-quality data. Get unbiased, real-world insights on Informatica data engineering solutions from peers you trust. Reference architectures for sustainable data engineering solutions. AI-powered data engineering in the cloud delivers the trusted, high quality data your analysts and data scientists need to transform business. -
17
Qlik Compose
Qlik
Qlik Compose for Data Warehouses provides a modern approach by automating and optimizing data warehouse creation and operation. Qlik Compose automates designing the warehouse, generating ETL code, and quickly applying updates, all whilst leveraging best practices and proven design patterns. Qlik Compose for Data Warehouses dramatically reduces the time, cost and risk of BI projects, whether on-premises or in the cloud. Qlik Compose for Data Lakes automates your data pipelines to create analytics-ready data sets. By automating data ingestion, schema creation, and continual updates, organizations realize faster time-to-value from their existing data lake investments. -
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Hazelcast
Hazelcast
In-Memory Computing Platform. The digital world is different. Microseconds matter. That's why the world's largest organizations rely on us to power their most time-sensitive applications at scale. New data-enabled applications can deliver transformative business power – if they meet today’s requirement of immediacy. Hazelcast solutions complement virtually any database to deliver results that are significantly faster than a traditional system of record. Hazelcast’s distributed architecture provides redundancy for continuous cluster up-time and always available data to serve the most demanding applications. Capacity grows elastically with demand, without compromising performance or availability. The fastest in-memory data grid, combined with third-generation high-speed event processing, delivered through the cloud. -
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Google Cloud Dataflow
Google
Unified stream and batch data processing that's serverless, fast, and cost-effective. Fully managed data processing service. Automated provisioning and management of processing resources. Horizontal autoscaling of worker resources to maximize resource utilization. OSS community-driven innovation with Apache Beam SDK. Reliable and consistent exactly-once processing. Streaming data analytics with speed. Dataflow enables fast, simplified streaming data pipeline development with lower data latency. Allow teams to focus on programming instead of managing server clusters as Dataflow’s serverless approach removes operational overhead from data engineering workloads. Allow teams to focus on programming instead of managing server clusters as Dataflow’s serverless approach removes operational overhead from data engineering workloads. Dataflow automates provisioning and management of processing resources to minimize latency and maximize utilization. -
20
Metrolink
Metrolink.ai
A high -performance unified platform which is layered on any existing infrastructure for seamless onboarding. Metrolink’s intuitive design empowers any organization to govern its data integration by arming it with advanced manipulations aimed to maximize diverse and complex data, refocus human resources, and eliminate overhead. Diverse, complex, multi-source, streaming data with rapidly changing use cases. Spending much more of the talent on data utilities, losing the focus on the core business. Metrolink is a Unified platform that allows organization design and manage their data pipelines according to their business requirements. This by enabling intuitive UI, advanced manipulations on diverse & complex data with high performance, in a way that amplifies data value while leveraging all data functions and data privacy in the organization. -
21
Datazoom
Datazoom
Improving the experience, efficiency, and profitability of streaming video requires data. Datazoom enables video publishers to better operate distributed architectures through centralizing, standardizing, and integrating data in real-time to create a more powerful data pipeline and improve observability, adaptability, and optimization solutions. Datazoom is a video data platform that continually gathers data from endpoints, like a CDN or a video player, through an ecosystem of collectors. Once the data is gathered, it is normalized using standardized data definitions. This data is then sent through available connectors to analytics platforms like Google BigQuery, Google Analytics, and Splunk and can be visualized in tools such as Looker and Superset. Datazoom is your key to a more effective and efficient data pipeline. Get the data you need in real-time. Don’t wait for your data when you need to resolve an issue immediately. -
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Conduktor
Conduktor
We created Conduktor, the all-in-one friendly interface to work with the Apache Kafka ecosystem. Develop and manage Apache Kafka with confidence. With Conduktor DevTools, the all-in-one Apache Kafka desktop client. Develop and manage Apache Kafka with confidence, and save time for your entire team. Apache Kafka is hard to learn and to use. Made by Kafka lovers, Conduktor best-in-class user experience is loved by developers. Conduktor offers more than just an interface over Apache Kafka. It provides you and your teams the control of your whole data pipeline, thanks to our integration with most technologies around Apache Kafka. Provide you and your teams the most complete tool on top of Apache Kafka. -
23
Crux
Crux
Find out why the heavy hitters are using the Crux external data automation platform to scale external data integration, transformation, and observability without increasing headcount. Our cloud-native data integration technology accelerates the ingestion, preparation, observability and ongoing delivery of any external dataset. The result is that we can ensure you get quality data in the right place, in the right format when you need it. Leverage automatic schema detection, delivery schedule inference, and lifecycle management to build pipelines from any external data source quickly. Enhance discoverability throughout your organization through a private catalog of linked and matched data products. Enrich, validate, and transform any dataset to quickly combine it with other data sources and accelerate analytics. -
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BigBI
BigBI
BigBI enables data specialists to build their own powerful big data pipelines interactively & efficiently, without any coding! BigBI unleashes the power of Apache Spark enabling: Scalable processing of real Big Data (up to 100X faster) Integration of traditional data (SQL, batch files) with modern data sources including semi-structured (JSON, NoSQL DBs, Elastic, Hadoop), and unstructured (Text, Audio, video), Integration of streaming data, cloud data, AI/ML & graphs -
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BettrData
BettrData
Our automated data operations platform will allow businesses to reduce or reallocate the number of full-time employees needed to support their data operations. This is traditionally a very manual and expensive process, and our product packages it all together to simplify the process and significantly reduce costs. With so much problematic data in business, most companies cannot give appropriate attention to the quality of their data because they are too busy processing it. By using our product, you automatically become a proactive business when it comes to data quality. With clear visibility of all incoming data and a built-in alerting system, our platform ensures that your data quality standards are met. We are a first-of-its-kind solution that has taken many costly manual processes and put them into a single platform. The BettrData.io platform is ready to use after a simple installation and several straightforward configurations. -
26
Adele
Adastra
Adele is an intuitive platform designed to simplify the migration of data pipelines from any legacy system to a target platform. It empowers users with full control over the functional migration process, while its intelligent mapping capabilities offer valuable insights. By reverse-engineering data pipelines, Adele creates data lineage mappings and extracts metadata, enhancing visibility and understanding of data flows. -
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Lightbend
Lightbend
Lightbend provides technology that enables developers to easily build data-centric applications that bring the most demanding, globally distributed applications and streaming data pipelines to life. Companies worldwide turn to Lightbend to solve the challenges of real-time, distributed data in support of their most business-critical initiatives. Akka Platform provides the building blocks that make it easy for businesses to build, deploy, and run large-scale applications that support digitally transformative initiatives. Accelerate time-to-value and reduce infrastructure and cloud costs with reactive microservices that take full advantage of the distributed nature of the cloud and are resilient to failure, highly efficient, and operative at any scale. Native support for encryption, data shredding, TLS enforcement, and continued compliance with GDPR. Framework for quick construction, deployment and management of streaming data pipelines. -
28
CData Sync
CData Software
CData Sync is a universal data pipeline that delivers automated continuous replication between hundreds of SaaS applications & cloud data sources and any major database or data warehouse, on-premise or in the cloud. Replicate data from hundreds of cloud data sources to popular database destinations, such as SQL Server, Redshift, S3, Snowflake, BigQuery, and more. Configuring replication is easy: login, select the data tables to replicate, and select a replication interval. Done. CData Sync extracts data iteratively, causing minimal impact on operational systems by only querying and updating data that has been added or changed since the last update. CData Sync offers the utmost flexibility across full and partial replication scenarios and ensures that critical data is stored safely in your database of choice. Download a 30-day free trial of the Sync application or request more information at www.cdata.com/sync -
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SynctacticAI
SynctacticAI Technology
Use cutting-edge data science tools to transform your business outcomes. SynctacticAI crafts a successful adventure out of your business by leveraging advanced data science tools, algorithms and systems to extract knowledge and insights from any structured and unstructured sets of data. Discover your data in any form – structure or unstructured and batch or real-time.Sync Discover is a key feature to discover a relevant piece of data and organizing the large pool of data in a systematic manner. Process your data at scale with Sync Data. Enabled with a simple navigation interface like drag and drop, you can smoothly configure your data pipelines and process data manually or at predetermined schedules. With the power of machine learning, the process of learning from data becomes effortless. Simply select the target variable, feature, and any of our pre-built models – rest is automatically taken care of by Sync Learn. -
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Apache Airflow
The Apache Software Foundation
Airflow is a platform created by the community to programmatically author, schedule and monitor workflows. Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers. Airflow is ready to scale to infinity. Airflow pipelines are defined in Python, allowing for dynamic pipeline generation. This allows for writing code that instantiates pipelines dynamically. Easily define your own operators and extend libraries to fit the level of abstraction that suits your environment. Airflow pipelines are lean and explicit. Parametrization is built into its core using the powerful Jinja templating engine. No more command-line or XML black-magic! Use standard Python features to create your workflows, including date time formats for scheduling and loops to dynamically generate tasks. This allows you to maintain full flexibility when building your workflows.
