Best Data Lineage Tools Comparison

    Best Data Lineage Tools Comparison

    Before discussing data lineage tools comparison, let’s understand the data lineage tool.
    Data analysis is critical, and for that, data lineage tools are best.
    Conversely, data lineage tools are software systems that assist companies and data analysts in understanding the source of their data and how it has evolved.

    Best Data Lineage Tools Comparison

    What is a data lineage tool?

    Data lineage discovers the life cycle of data. Therefore, it aims to present the complete data flow from start to finish. Data lineage is the process of understanding, reporting, and visualizing data flows from data sources to consumption. That includes all transformations the data underwent along the way.
    Data lineage enables companies to:

    • Track errors in data processes
    • Execute process changes with lower risk
    • Work on system migrations with confidence
    • Combine data discovery with a broad view of metadata to build a data mapping framework

    Therefore, it also helps users ensure their data comes from a trusted source, is transformed correctly, and stored to the specified location. Thus, it plays a crucial role when strategic decisions rely on accurate information. However, if data processing tracking isn’t valid, data becomes almost unmanageable or very costly, and time-consuming to verify.
    Hence, data lineage concentrates on validating data accuracy and consistency by enabling users to explore upstream and downstream, from source to destination, to identify irregularities and correct them.

    Data lineage techniques

    Pattern-Based Lineage

    It performs lineage without dealing with the code used to produce or modify the data. Hence, it requires the evaluation of metadata for tables, columns, and business reports. So, using this metadata, it examines lineage by looking for patterns.
    Therefore, the notable advantage of pattern-based lineage is that it only observes data, not data processing algorithms, so it is technology agnostic. Hence, it can be utilized in the same approach across any database technology, whether Oracle, MySQL, or Spark.
    The disadvantage is that this method is not always correct. It can sometimes miss connections between datasets, especially if the data processing logic is hidden in the programming code and not possible in human-readable metadata.

    Lineage by Data Tagging

    This technique is based on the thought that a transformation engine tags or records data in some way. Thus, to determine lineage, it tracks the tag from start to finish. Therefore, this method is only helpful if one has a steady transformation tool that manages all data movement and knows the tagging structure used by the device.
    Moreover, lineage via data tagging cannot get employed to any data generated or transformed without the tool if such a tool exists. Hence, it is only proper for performing data lineage on closed data systems.

    Self-Contained Lineage

    Some organizations have a data environment that gives storage, processing logic, and master data management to centralize metadata. However, these environments include a data lake that stores all data in all stages of its lifecycle.
    Therefore, this type of self-contained system can essentially provide lineage without the need for external tools. Still, with the data tagging approach, lineage will be ignorant of anything outside this controlled environment.

    Lineage by Parsing

    Lineage by Parsing is the most advanced form of lineage, which automatically reads the logic and processes data. Hence, this technique reverses the engineer’s data transformation logic to perform comprehensive, end-to-end tracing.
    Hence, this solution is complicated to deploy because it requires understanding all the programming languages and tools utilized to transform and move the data. Moreover, this includes extract-transform-load (ETL) logic, SQL-based solutions, JAVA solutions, legacy data formats, XML-based solutions, and so on.

    Data Lineage Tools Comparison


    OvalEdge is a combination of a data governance and data catalog toolset. Hence, its usage is to understand, find, govern, and regulate data. Additionally, the tool helps one to deliver insights in the best ways.
    Therefore, the software crawls one’s system database to collect all available data to create a catalog. Thus, it indexes all this data and draws a lineage that shows the complete data cycle.
    Furthermore, the data is in an organized manner to easily access each one and get a data summary for easier comprehension.
    Besides, it employs different data management platforms, business intelligence, and analytical platforms.
    Key Features

    • It is used via the web as it’s cloud-based or installed on Windows and Linux computers.
    • OvalEdge discovers data and delivers powerful insights quickly.
    • Also enables users to establish and improve data access, data literacy, and data quality.


    • Starter Package – $100 per month per user
    • Other Packages – Custom pricing


    CloverDX is a conventional data lineage tool developed to solve data challenges. Prominently, the tool is perfect for enterprise data management.
    Additionally, CloverDX features a developer-friendly visual designer. Thus, this is most helpful to data novices as it makes the entire data design method not appear complex. Therefore, the tool is ideal for data migration as repeatable tasks can be automated.
    Therefore, it also cleans data and helps fix any error, so consistency is not affected. Hence, it is available on Cloud, Windows, and Mac.
    Key Features

    • Makes data available to people, applications, and storage under a single unified platform.
    • Developer-friendly open architecture and flexibility let you package and hide the complexity for non-technical users.


    • Starting Price: $5000.00/one-time


    Alation is a data intelligence software launched in 2012. It is AI-driven and can support data discovery, data lineage and governance, and transformation. Thus, the software works with a native cloud service, the Alation Cloud Service, which permits faster delivery.
    Therefore, it also features an advanced behavioral analysis engine that identifies the most profound insights. Thus, with guided navigation, anyone can use this software seamlessly.
    Moreover, it follows a people-first approach, and cataloging, data classification, and stewardship can all be automated.
    Moreover, the software automatically produces quality flags, warnings, etc., to help one make the best decisions.
    Alation is popular amongst top organizations like PepsiCo, Motorola, ComED, etc.
    Key Features

    • It improves the productivity of analysts.
    • Also improves the accuracy of analytics.
    • Empowers better business decisions.

    After creating an account and scheduling a demo, one can discuss with the sales team a suitable pricing plan. Note that Alation charges per feature.


    Datameer gives data and analytics solutions to all industries. Therefore, it is a data lineage tool for multiple individuals and businesses because it is simple, and their team provides quality support. Thus, the platform features two main products: Datameer Spotlight and Datameer Spectrum. Both are data engineering solutions.
    With Datameer products, one has to access tools for discovering, accessing, modeling, and delivering data. Modeling and building data pipelines with Datameer needs no coding. Hence, it’s a complete visual process, and one can count on its efficiency.
    Moreover, it’s straightforward to discover the tools/data one needs, thanks to the Google-like search engine. One can use the Datameer tool in other cloud solutions, such as Microsoft Azure, Amazon AWS, and Google Cloud.
    Key Features

    • It is a SaaS data transformation solution for snowflake data warehouses.
    • It has a no-code interface.


    • Personal Edition – $300 per year
    • Workgroup Edition – $19,188 per year
    • Enterprise Edition – Custom pricing


    Atlan serves as a modern data workspace for data lineage, catalog, quality, and exploration. It is for non-technical users with an open API architecture and is quick to deploy.
    With Atlan, one can quickly discover all the data assets with the help of solid search algorithms. Moreover, the software’s interface is intuitive and comparatively easy to navigate. Therefore, one can immediately discover assets like intelligence reports and data tables.
    The Atlan bot automatically performs data lineage. Atlan combines with several third-party platforms, including Snowflake, Amazon S3, Amazon Redshift, Azure, Google Cloud, MySQL, Tableau, etc.
    Key Features

    • Atlan auto-generates data quality profiles, which makes detecting insufficient data, dead easy.


    • Starter Package – Up to 500 data assets
    • Premier Package – Up to 3000 data assets
    • Enterprise Package – Unlimited data assets


    With truedat, one can turn the data into a valuable business asset. Bluetab Solutions developed this software.
    Thus, it operates for cloud ingestion, data lake governance, data quality, etc. Some top organizations that use truedat are LaLiga, Telcel, BMN, Naturgy, and Bankia.
    Therefore, it provides a solution for end-to-end data governance that includes both data lineage and data quality. Besides, one can switch from a technical view to a simple business view. Hence, the software is ideal for novices and experts.
    Truedat unites with other third-party tools, including MicroStrategy, Google BigQuery, Microsoft Azure, Oracle, Hive, Power BI, Amazon Redshift, and more.
    Key Features

    • It helps to define business processes, roles & responsibilities.
    • It also helps to put processes into practice.


    • Free to use


    Launched by Teradata, Kylo is a unique software for building data pipelines. The software has five key features: ingesting, preparing, discovering, monitoring, and designing data. Therefore, it is applicable as a data lake platform.
    Also, it has features for metadata management, data governance, and data security. Hence, it’s an open-source software which makes it an advantage for programmers.
    Moreover, with the simple guided user interface (UI), data ingestion is seamless. There’s the transformation characteristic for preparing data, and Kylo also practices Apache Spark. Thus, Kylo features modern methods of monitoring feeds.
    Key Features

    • It features a pipeline template mechanism that makes it possible to connect it with any data source, format, and deploy data into any target.
    • It monitors the health of feeds and services in the data lake.
    • Tracks SLAs and troubleshoot performance.


    • Free to use


    Data lineage is essential if one wants to do reproducible, high-quality work. Many data lineage tools are available, but one needs to choose the best one with the right features depending upon the requirements. With these tools, one will properly audit data from its origin to the current endpoint.

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