Best Data Lineage Tools for SQL Server

Find and compare the best Data Lineage tools for SQL Server in 2024

Use the comparison tool below to compare the top Data Lineage tools for SQL Server on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Datameer Reviews
    Datameer is your go-to data tool for exploring, preparing, visualizing, and cataloging Snowflake insights. From exploring raw datasets to driving business decisions – an all-in-one tool.
  • 2
    Immuta Reviews
    Immuta's Data Access Platform is built to give data teams secure yet streamlined access to data. Every organization is grappling with complex data policies as rules and regulations around that data are ever-changing and increasing in number. Immuta empowers data teams by automating the discovery and classification of new and existing data to speed time to value; orchestrating the enforcement of data policies through Policy-as-code (PaC), data masking, and Privacy Enhancing Technologies (PETs) so that any technical or business owner can manage and keep it secure; and monitoring/auditing user and policy activity/history and how data is accessed through automation to ensure provable compliance. Immuta integrates with all of the leading cloud data platforms, including Snowflake, Databricks, Starburst, Trino, Amazon Redshift, Google BigQuery, and Azure Synapse. Our platform is able to transparently secure data access without impacting performance. With Immuta, data teams are able to speed up data access by 100x, decrease the number of policies required by 75x, and achieve provable compliance goals.
  • 3
    Dataedo Reviews

    Dataedo

    Dataedo

    $49 per month
    Your metadata can be discovered, documented and managed. Dataedo has multiple automated metadata scanners. These scanners connect to different database technologies, extract data structures, and then load them into the metadata repository. In just a few clicks you can create a catalog of all your data and then describe each element. With business-friendly aliases, decrypt column and table names and provide meaning and purpose to data assets with descriptions and custom fields. To find out what data is stored in your data asset, you can use sample data. Make sure you have a better understanding of the data before you use it. Data profiling can help ensure high quality data. Data profiling allows everyone to have access to data knowledge. A lightweight, on-premises data catalogue can help you build data literacy, democratize data, and empower your employees to make better data use. A data catalog can help you increase data literacy.
  • 4
    Weld Reviews

    Weld

    Weld

    €750 per month
    Your data models can be created, edited, and organized. You don't need another data tool to manage your data models. Weld allows you to create and manage them. It is packed with features that make it easy to create your data models: smart autocomplete, code folding and error highlighting, audit logs and version control, collaboration, and version control. We use the same text editor that VS Code - it is fast, powerful, and easy to read. Your queries are organized in a searchable and easily accessible library. Audit logs allow you to see when and by whom the query was last updated. Weld Model allows you to materialize models as views, tables, incremental tables, and views. You can also create custom materializations of your design. With the help of a dedicated team, you can manage all your data operations from one platform.
  • 5
    Ataccama ONE Reviews
    Ataccama is a revolutionary way to manage data and create enterprise value. Ataccama unifies Data Governance, Data Quality and Master Data Management into one AI-powered fabric that can be used in hybrid and cloud environments. This gives your business and data teams unprecedented speed and security while ensuring trust, security and governance of your data.
  • 6
    Metaplane Reviews

    Metaplane

    Metaplane

    $825 per month
    In 30 minutes, you can monitor your entire warehouse. Automated warehouse-to-BI lineage can identify downstream impacts. Trust can be lost in seconds and regained in months. With modern data-era observability, you can have peace of mind. It can be difficult to get the coverage you need with code-based tests. They take hours to create and maintain. Metaplane allows you to add hundreds of tests in minutes. Foundational tests (e.g. We support foundational tests (e.g. row counts, freshness and schema drift), more complicated tests (distribution shifts, nullness shiftings, enum modifications), custom SQL, as well as everything in between. Manual thresholds can take a while to set and quickly become outdated as your data changes. Our anomaly detection algorithms use historical metadata to detect outliers. To minimize alert fatigue, monitor what is important, while also taking into account seasonality, trends and feedback from your team. You can also override manual thresholds.
  • 7
    Secoda Reviews

    Secoda

    Secoda

    $50 per user per month
    Secoda AI can help you generate documentation and queries from your metadata. This will save your team hundreds of hours of tedious work. Secoda AI will also generate documentation and queries based on your metadata. This will save your team hundreds of tedious hours and redundant data requests. Search across all columns, dashboards and metrics, as well as tables, dashboards and tables. AI-powered searches allow you to ask any question and receive a contextual response quickly. Answer questions. Our API allows you to integrate data discovery into your workflow, without disrupting the flow. Perform bulk updates, tag PII, manage tech debt and more. Eliminate manual errors and have complete trust in your knowledge base.
  • 8
    Secuvy AI Reviews
    Secuvy, a next-generation cloud platform, automates data security, privacy compliance, and governance via AI-driven workflows. Unstructured data is treated with the best data intelligence. Secuvy, a next-generation cloud platform that automates data security, privacy compliance, and governance via AI-driven workflows is called Secuvy. Unstructured data is treated with the best data intelligence. Automated data discovery, customizable subjects access requests, user validations and data maps & workflows to comply with privacy regulations such as the ccpa or gdpr. Data intelligence is used to locate sensitive and private information in multiple data stores, both in motion and at rest. Our mission is to assist organizations in protecting their brand, automating processes, and improving customer trust in a world that is rapidly changing. We want to reduce human effort, costs and errors in handling sensitive data.
  • 9
    AnalyticsCreator Reviews
    AnalyticsCreator lets you extend and adjust an existing DWH. It is easy to build a solid foundation. The reverse engineering method of AnalyticsCreator allows you to integrate code from an existing DWH app into AC. So, more layers/areas are included in the automation. This will support the change process more extensively. The extension of an manually developed DWH with an ETL/ELT can quickly consume resources and time. Our experience and studies found on the internet have shown that the longer the lifecycle the higher the cost. You can use AnalyticsCreator to design your data model and generate a multitier data warehouse for your Power BI analytical application. The business logic is mapped at one place in AnalyticsCreator.
  • 10
    Truedat Reviews

    Truedat

    Bluetab Solutions

    Bluetab Solutions developed Truedat, an open-source data governance business solution tool. It was created to help our clients become data-driven businesses. We assist in defining business processes, roles and responsibilities. We can also help you put these processes into action. Integration and customization of truedat’s open-source components to support data governance processes. We guarantee the maintenance and support of the solution modules we have installed. Based on our extensive experience, we have created a solution that addresses the need for Data Governance. This allows you to manage complex and changing data architectures. Truedat is becoming more important due to the increasing migration of enterprise IT platforms into cloud, multi-cloud, hybrid architectures. This increases the complexity, sources, and types of data. Our Data Governance consulting and development experience spans more than 8 years.
  • 11
    Sifflet Reviews
    Automate the automatic coverage of thousands of tables using ML-based anomaly detection. 50+ custom metrics are also available. Monitoring of metadata and data. Comprehensive mapping of all dependencies between assets from ingestion to reporting. Collaboration between data consumers and data engineers is enhanced and productivity is increased. Sifflet integrates seamlessly with your data sources and preferred tools. It can run on AWS and Google Cloud Platform as well as Microsoft Azure. Keep an eye on your data's health and notify the team if quality criteria are not being met. In a matter of seconds, you can set up the basic coverage of all your tables. You can set the frequency, criticality, and even custom notifications. Use ML-based rules for any anomaly in your data. There is no need to create a new configuration. Each rule is unique because it learns from historical data as well as user feedback. A library of 50+ templates can be used to complement the automated rules.
  • 12
    Validio Reviews
    Get a clear view of your data assets: popularity, usage, and schema coverage. Get important insights into your data assets, such as popularity and utilization. Find and filter data based on tags and descriptions in metadata. Get valuable insights about your data assets, such as popularity, usage, quality, and schema cover. Drive data governance and ownership throughout your organization. Stream-lake-warehouse lineage to facilitate data ownership and collaboration. Lineage maps are automatically generated at the field level to help understand the entire data ecosystem. Anomaly detection is based on your data and seasonality patterns. It uses automatic backfilling from historical data. Machine learning thresholds are trained for each data segment and not just metadata.
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