Best Data Catalog Software for PostgreSQL

Composable is an enterprise-grade DataOps platform designed for business users who want to build data-driven products and create data intelligence solutions. It can be used to design data-driven products that leverage disparate data sources, live streams, and event data, regardless of their format or structure. Composable offers a user-friendly, intuitive dataflow visual editor, built-in services that facilitate data engineering, as well as a composable architecture which allows abstraction and integration of any analytical or software approach. It is the best integrated development environment for discovering, managing, transforming, and analysing enterprise data.

PopSQL is the evolution of legacy SQL editors like DataGrip, DBeaver, Postico. We provide a beautiful, modern SQL editor for data focused teams looking to save time, improve data accuracy, onboard new hires faster, and deliver insights to the business fast. With PopSQL, users can easily understand their data model, write version controlled SQL, collaborate with live presence, visualize data in charts and dashboards, schedule reports, share results, and organize foundational queries for search and discovery. Even if your team is already leveraging a large BI tool, like Tableau or Looker, or a hodge podge of SQL editors, PopSQL enables seamless collaboration between your SQL power users, junior analysts, and even your less technical stakeholders who are hungry for data insights. * Cross-platform compatibility with macOS, Windows, and Linux * Works with Snowflake, Redshift, BigQuery, Clickhouse, Databricks, Athena, MongoDB, PostgreSQL, MySQL, SQL Server, SQLite, Presto, Cassandra, and more

DvSum, an AI-powered Data Intelligence platform, makes it remarkably easy for data and analytics teams discover, monitor, and govern data. DvSum uses powerful AI-enabled algorithms to automatically catalog, classify, and curate your data and make it available as a Data Catalog. DvSum Data Intelligence will help you propel your enterprise towards its digital- and analytics-enabled transformation goals.

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.

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.

Decube is a comprehensive data management platform designed to help organizations manage their data observability, data catalog, and data governance needs. Our platform is designed to provide accurate, reliable, and timely data, enabling organizations to make better-informed decisions. Our data observability tools provide end-to-end visibility into data, making it easier for organizations to track data origin and flow across different systems and departments. With our real-time monitoring capabilities, organizations can detect data incidents quickly and reduce their impact on business operations. The data catalog component of our platform provides a centralized repository for all data assets, making it easier for organizations to manage and govern data usage and access. With our data classification tools, organizations can identify and manage sensitive data more effectively, ensuring compliance with data privacy regulations and policies. The data governance component of our platform provides robust access controls, enabling organizations to manage data access and usage effectively. Our tools also allow organizations to generate audit reports, track user activity, and demonstrate compliance with regulatory requirements.

Castor is a data catalogue that can be adopted by all employees. Get a complete overview of your data environment. Our powerful search engine makes it easy to find data quickly. Access data quickly and easily by joining a new data infrastructure. Expand beyond the traditional data catalog. Modern data teams have multiple data sources. Instead of building one truth, they build it. Castor's delightful and automated documentation makes it easy to trust data. In minutes, you can get a column-level view of your cross-system data lineage. To build trust in your data, get a bird's-eye view of your data pipelines. All you need to troubleshoot data issues, conduct impact analyses, and comply with GDPR is one tool. Optimize performance, cost compliance, security, and security for data. Our automated infrastructure monitoring system will keep your data stack healthy.

Y42 is the first fully managed Modern DataOps Cloud for production-ready data pipelines on top of Google BigQuery and Snowflake.

Fully managed and highly scalable metadata and data discovery service. New customers receive $300 in Google Cloud credits for free during the Free Trial. All customers receive up to 1 MiB business or ingested meta data storage and 1,000,000 API calls free of charge. A simple, but powerful faceted search interface allows you to pinpoint your data. Automatically sync technical metadata and create schematized tags to support business metadata. Cloud Data Loss Prevention integration allows you to automatically tag sensitive data. Access your data immediately and scale without the need to manage or set up infrastructure. With a powerful UI built with the same search technology that Gmail or API access, empower any member of the team to find and tag data. Data Catalog is fully managed so that you can easily start and scale. Cloud IAM integrations and Cloud DLP integrations allow you to enforce data security policies and ensure compliance.

Tableau Catalog is a benefit for everyone. Tableau Catalog provides a complete view of the data and how it connects to the analytics in Tableau. This increases trust and discoverability for IT and business users. Tableau Catalog makes it easy to communicate changes to the data, review dashboards, or search for the right data for analysis. Tableau Catalog automatically ingests all data assets in your Tableau environment into a single central list. There is no need to create an index schedule or connect. You can quickly see all of your files, tables, and databases in one location. Migration of databases, deprecating fields or adding a column to a table can all have potential impacts on your environment. Lineage and impact analysis allows you to see not only the upstream and downstream implications of assets but also who will be affected.

ThinkData Works provides a robust catalog platform for discovering, managing, and sharing data from both internal and external sources. Enrichment solutions combine partner data with your existing datasets to produce uniquely valuable assets that can be shared across your entire organization. The ThinkData Works platform and enrichment solutions make data teams more efficient, improve project outcomes, replace multiple existing tech solutions, and provide you with a competitive advantage.

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.

Datafi is a platform that provides a unified data environment for business teams. It integrates data silos, unifies data security, and enables self-service workflows to meet the unique needs of business users who want to find, use, or share the information they need. Datafi is used by customers to increase their organization's data capabilities, and empower more employees to make better and faster data-driven decision. Datafi makes data easily accessible and meaningful to everyone. Know how your data will be accessed and used. Data-forward companies know how important it is to enable their data to drive business outcomes. This starts with enabling easy and secure data access. Data-driven insights can lead to new business outcomes. Organizations that improve their data literacy will be more likely to discover these data-driven insights.

Alteryx AI Platform will help you enter a new age of analytics. Empower your organization through automated data preparation, AI powered analytics, and accessible machine learning - all with embedded governance. Welcome to a future of data-driven decision making for every user, team and step. Empower your team with an intuitive, easy-to-use user experience that allows everyone to create analytical solutions that improve productivity and efficiency. Create an analytics culture using an end-toend cloud analytics platform. Data can be transformed into insights through self-service data preparation, machine learning and AI generated insights. Security standards and certifications are the best way to reduce risk and ensure that your data is protected. Open API standards allow you to connect with your data and applications.

You can unify your data catalog, reduce communication overhead, and enable quality control for any employee of your company without having to deploy or install anything. Rudol is a data platform that helps companies understand all data sources, regardless of where they are from. It reduces communication in reporting processes and urgencies and allows data quality diagnosis and issue prevention for all company members. Each organization can add data sources from rudol's growing list of providers and BI tools that have a standardized structure. This includes MySQL, PostgreSQL. Redshift. Snowflake. Kafka. S3*. BigQuery*. MongoDB*. Tableau*. PowerBI*. Looker* (*in development). No matter where the data comes from, anyone can easily understand where it is stored, read its documentation, and contact data owners via our integrations.

For your analysis and modeling, discover and trust data. Breaking down silos can help you be more productive. See how others are using the data to get context. A simple text search can be used to find data within your organization. A PageRank-inspired search algorithm suggests results based upon names, descriptions, tags and querying/viewing activity at the table/dashboard. Automated and curated metadata, descriptions and columns of tables and columns, other frequent users, the date the table was last updated, statistics and a preview of data, can help build trust in data. Easy triage by linking ETL job and the code that generated the data. Update tables and columns with descriptions to reduce back-and-forth about which table to use or what a column contains. Find out what data coworkers use, own, or have saved. You can see dashboards created on a table to show you the most common queries.

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.

No more data catalog ghost cities. Acryl Cloud accelerates time-to-value for data producers through Shift Left practices and an intuitive user interface for data consumers. Continuously detect data-quality incidents in real time, automate anomaly detecting to prevent breakdowns, and drive quick resolution when they occur. Acryl Cloud supports both pull-based and push-based metadata ingestion to ensure information is reliable, current, and definitive. Data should be operational. Automated Metadata Tests can be used to uncover new insights and areas for improvement. They go beyond simple visibility. Reduce confusion and speed up resolution with clear asset ownership and automatic detection. Streamlined alerts and time-based traceability are also available.

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.