5 Best Data Management Tools [2024 Buyer’s Guide]

During COVID-19, the volume of data created and copied peaked due to increased demand, as more people worked and learned from home. In the intervening years, that volume has only exploded expontentially, and the intelligent solutions needed to handle it have lagged behind.

Teams need efficient data management to have a competitive edge. But in a crowded market, which tools can automate repetitive tasks and maintain data asset security?

Before choosing any data management tool, you must understand its features, benefits, costs, and other key considerations. Let's explore. 

Need to understand all the tools teams are using to manage data? Use this data tech stack audit and survey template to get started.

A quick cheat sheet: 

• data.world: Best for data discovery and governance

• Talend: Ideal for companies that need data integration

• Informatica: Suitable for use as a master data management tool

• SAP: Best to be used as an enterprise data management tool in large organizations

• Snowflake: Perfect for cloud data management in organizations with cloud-based data architectures

Now, let’s explore these data management tools in detail to help you choose the right one for your business

Data management tools help organizations manage and use their data.

With an efficient data management tool, organizations can structure their data so it is readily accessible to different departments.

Want to know where the future of data management is heading? Check out this podcast.

Data management tools help you with the following:

• Providing a strong security framework to protect sensitive information from unauthorized access and breaches

• Automating data handling processes to save time and reduce manual effort while streamlining operations

• Giving teams quick access to high-quality data

• Enabling master data management to reduce data storage and maintenance costs 

• Adhering to legal and regulatory standards to prevent possible fines

• Managing the growing volumes of data to scale operations without compromising performance

We can break down data management tools into five distinct categories:

Data Integration tools gather data from different sources, whether on-premise or cloud. These tools have ETL (Extract, Transform, Load) capabilities which help with the following:

• Extracting data from various sources

• Transforming it into a suitable format

• Loading it into a destination system, such as a data warehouse

Master data management tools manage an organization’s critical data to provide a single point of reference. They give users the authority to access the most relevant data, directly from the source. They also handle repetitive data operations to ensure consistency and uniformity.

Data warehousing tools store structured data for reporting and analysis. Similarly, data lake tools handle large volumes of raw data that can be structured, semi-structured, or unstructured and saved in a repository.

Data cataloging and governance tools like data.world are specially responsible for providing an organization with a structured inventory of data assets. They help with:

• Making data discovery more accessible and automated for data scientists and analysts

• Tracking the origins and transformations of data for audit and compliance 

• Enforcing data governance policies according to regulations

Data visualization and analytics tools transform raw data into interactive visual formats. They allow users to create tables, charts, and dashboards that update in real-time.

Here are 5 of the best data management tools currently available on the market. They have been selected for their exceptional ability to meet diverse data management needs.

data.world tops this list with the best data cataloging and governance solutions in the market. As a cloud-native SaaS platform, it is designed to support the future of AI. 

With its AI-context-rich engine, data.world provides advanced data discovery capabilities that make it faster than ever to analyze your data. It handles scaling and infrastructure with no hidden costs and continuous feature releases. 

With a powerful knowledge graph to connect and understand data relationships, you get better insights and data discovery here. 

Here are the features and capabilities that make data.world a top choice for customers:

• Enterprise Data Catalog: Organizes and manages metadata to make it simple for users to search and share data across the organization

• Knowledge Graph: Connects and contextualizes data relationships which gives a comprehensive view of data assets and their interconnections

• Self-Service Analytics: Allows users to perform their data analysis without having high-level technical expertise

• Data Governance: Provides a complete security and compliance framework to automate data-related tasks

• AI-powered Search: Makes data discovery 10x faster than manual searching with a knowledge graph-based, context-aware search engine

Since data.world is a versatile data management tool that excels in various scenarios, it benefits organizations with the following makeup:

1. Organizations with complex data landscapes:

   It’s ideal for organizations with complex data architectures because it can simplify data management by integrating diverse data sources into a unified data catalog.

2. Companies seeking to democratize data access:

   It is best for businesses that want to democratize data access as it allows easy and secure access for all users based on their roles.

3. Businesses aiming to improve data governance:

   It is ideal for companies that need to improve data governance, as it can provide automation tools to handle all data management tasks.

4. Large enterprises with modern data stacks:

   It is best for large, complex organizations as it is a modern, cloud-native data cataloging platform that can be easily integrated into existing data architecture.

You can integrate data.world with the following platforms:

Cloud platforms:

• Amazon Web Services (AWS)

• Google Cloud Platform (GCP)

• Microsoft Azure

Data warehouses:

• Snowflake

• Google BigQuery

• Amazon Redshift

Business intelligence tools:

• Tableau

• Looker

• Power BI

data.world provides unmatched scalability and performance through its advanced cloud-native architecture. It can manage complex data environments and handle large datasets efficiently by ensuring the platform accommodates increased loads as your data requirements expand without compromising performance. 

Learn more about how data.world provides a next-generation data catalog for modern data management.

data.world has four main pricing tiers:

• Essentials: Consists of primary data cataloging features

• Standard: Provides full enterprise support and SLAs

• Enterprise: Provides data.world collector that is an on-premise, secure metadata collection agent

• Enterprise+: Gives customizing options for organizations that require advanced capabilities for special security needs

Talend is a Data Integration and Data Governance Tool. With its comprehensive suite of tools, it allows users to extract, transform, and load (ETL) data from diverse sources. Whether dealing with big data or traditional databases, it can efficiently clean and prepare entire datasets to produce accurate insights. 

• Data Integration: Connects and transforms data from various sources for comprehensive data integration

• Application Integration: Integrates applications and APIs to meet real-time business demands

• Data Quality: Combines data integration with quality checks to ensure that data is clean and reliable

• Data Governance: Provides data compliance and integrity tools to oversee regulatory checks

• Trust Score: Gives at-a-glance visibility into the reliability of datasets to help users quickly assess the quality of their data

1. Retail businesses with large data assets:

   For organizations who need systems for integrating customer data from various touchpoints to create a unified customer profile.

2. Hospitals and medical centers for patient records:

   For gathering patient records from different systems to maintain accurate and comprehensive patient information.

3. Data management for financial institutes:

   Talend is ideal for financial institutes like banks where big data needs to be aggregated from different financial systems. 

4. Supply chain data integration:

   For cases where data has to be integrated from suppliers and distribution networks, and exchanged between different departments.

You can integrate Talend with the following tools:

• AWS

• Microsoft Partner

• Cloudera

• Snowflake

• Databricks

• Google

• Chartio 

• Looker

• Tableau

Talend's cloud-native approach lets your data architecture adapt faster, and it is also a cost-effective solution. Talend efficiently handles large volumes of data and complex data environments. Moreover, it uses advanced data processing techniques to execute data operations quickly and reliably.

Talends provides the following 4 pricing tiers:

• Stitch: Provides no code data ingestion and data warehousing capabilities

• Data Management Platform: Provides integrations for multi/hybrid cloud and on-premises along with data profiling features

• Big Data Platform: Provides advanced analytics for cross-team collaboration

• Data Fabric: Contains all the data integration features and tools of Talend

Informatica provides AI-powered data management solutions. Its Intelligent Data Management Cloud™ (IDMC) is a multi-cloud hybrid modernation solution that helps increase the ROI of other technology investments within the org.

• Data Cataloging: Uses AI-powered tools to provide metadata-driven insights in an automated data catalog to find and classify data assets

• Cloud Data Integration: Provides a single data engineering solution to clean and integrate your data with ELT/ETL tools

• Data Governance: Enforces data policies and standards to maintain data quality and compliance

• Data Quality: Resolves data issues with trustworthy data analytics automated with AI

• Master Data Management: Collects and manages critical business data for a single source of truth

• Cloud Data Marketplace: Promotes data democratization by making it easy to share and use reliable data

• Cloud Application Integration: Allows quick integration of applications and APIs for data management

1. Department stores that require self-service analytics:

   Informatica is ideal for department stores for enabling self-service discoverable and accessible data consumption.

2. Point-to-point integration:

   Information works for companies that use point-to-point integration, because it can centralize all data flows using a hub-and-spoke model

3. Organizations that need to preserve resources:

   It can help organizations monitor and reduce resource consumption by configuring different data retention periods to minimize resource usage.

• SaaS Applications: Salesforce, Workday, and ServiceNow

• On-Premises Applications: SAP, Oracle, and Microsoft

• Cloud Services: AWS, Azure, and Google Cloud

Informatica can handle large data volumes while maintaining high performance and scalability. It can join multiple repositories with a single Web Services Hub and run multiple cases of web service workflows to balance the load. 

These features ensure that Informatica can scale to meet growing data demands and complex integrations.

Informatica does not have transparent pricing, but it provides a flexible pricing model that charges based on consumption. This means you can pay for data management services' actual usage, making it a cost-effective and scalable solution.

SAP's Master Data Governance platform is an enterprise data management tool. It's best for storing and handling large volumes of data, as SAP provides its data warehouses. It can centrally manage master data using the SAP Business Technology Platform.

• Data Integration: Tools like SAP Data Intelligence and SAP Data Services help integrate data from different sources.

• Data Quality: Ensures clean and accurate data through tools such as SAP HANA Smart Data Quality.

• Master Data Management (MDM): Manages and stores master data with solutions like SAP Master Data Governance.

• Data Warehousing: Gives options like SAP Business Warehouse, SAP BW/4HANA, and SAP Datasphere for structured data storage.

• Data Governance: Integrates your data from different systems into a single source where data is governed under standardized definitions and business rules.

• Big Data Management: Provides SAP Vora and integration with Hadoop for big data analytics.

• Lifecycle Management: Manages data lifecycle and archiving with SAP Information Lifecycle Management.

1. Businesses looking to govern their data:

   SAP works great for businesses that need good data governance. Tools like SAP HANA and SAP Analytics Cloud automate insights and help teams get organized

2. Human resource management with automated processes:

   SAP gives access to automation tools for managing employee data and recruitment processes for HR management

3. Financial management of large records:

   SAP can automate and optimize financial operations through accounting and treasury management

4. Warehouse record management in supply chains:

   SAP is used in supply chains to streamline procurement processes and supplier management

• SAP NetWeaver Process Integration

• HANA Cloud integration

• MuleSoft

SAP’s data management tools use in-memory computing technology to process data directly from memory rather than disk storage. SAP HANA also supports scale-up and scale-out architectures, allowing it to efficiently handle large volumes of data and concurrent users. 

SAP provides exact prices upon request, but its 5000 objects per year plan starts at $1044 USD.

Snowflake is a cloud-based data platform. It provides a scalable and fully elastic platform for managing data warehousing-related tasks. 

• Data Warehousing: Allows businesses to query and analyze large volumes of data efficiently

• Data Lakes: Stores any type of data in a scalable and cost-effective manner

• Data Sharing: Enables secure and governed data sharing between organizations and departments

• Data Engineering: Provides tools and capabilities for data engineering so data engineers can build and manage data pipelines

• Security and Governance: Provides complete data security and compliance with security features like encryption and data masking

1. Retail transaction analysis in stores:

   Snowflake is ideal for transactional analysis in retail stores, as it facilitates data transformation into usable formats

2. Data backup and recovery:

   Snowflake's "Time Travel" feature maintains 90-day backups for easy data recovery and analyzing data usage over different periods

3. Small data storage:

   Snowflake is also ideal for organizations that can't invest in ample data storage because it can automatically make micro-partitions in data 

4. Machine learning projects in AI-driven businesses

   Snowflake supports feature engineering with SQL, Python, Apache Spark, and ODBC/JDBC interfaces for efficient data processing

Business Intelligence (BI) Tools:

• Tableau

• Power BI

• Looker

• Qlik

• Sisense

ETL (Extract, Transform, Load) Tools:

• Informatica

• Talend

• Matillion

• Stitch

• Fivetran

• Alteryx

Data Governance and Cataloging Tools:

• Collibra

• Alation

• Immuta

• OvalEdge

Machine Learning and Data Science Tools:

• Dataiku

• Jupyter Notebooks

• Databricks

Data Storage and Cloud Platforms:

• Amazon S3

• Microsoft Azure Blob Storage

• Google Cloud Storage

• AWS

• Azure

• Google Cloud Platform (GCP)

Snowflake's architecture provides a multi-cluster, shared data architecture that separates compute and storage resources, making it a particularly useful tool for easy scaling. 

Snowflake's automation capabilities are particularly well-suited for jobs like ingestion and scheduling. Snowflake's easy automations reduce manual intervention and errors.

Snowflake has four different pricing options:

• Standard: Provides access to core functionalities of Snowflake at a $2.00/ per credit ($USD) rate

• Enterprise: Designed for companies that need to handle large-scale data, which costs $3.00/ per credit ($USD)

• Business Critical: Provides special features for managing sensitive data for $4.00/ per credit ($USD)

• Virtual Private Snowflake: Custom pricing plan that offers all the features of Snowflake in a separate private network

Different data management tools offer distinct features tailored to specific needs, from data integration and quality to big data and cloud management. Check out this list to get a sense of which features you want to prioritize: 

• Data Source Connectivity: Ability to connect to various data sources like databases, cloud storage, APIs, and files to integrate them into a unified storage

• Data Transformation Capabilities: Features to clean data and eliminate errors so that the quality is consistent

• ETL/ELT Process Management: Automate ETL processes to optimize workflows and reduce manual interventions

• Scheduling and Error Handling: Includes features to schedule data processing tasks and automatically handle errors 

• Scalability and Performance: Ability to handle increasing volumes of data and maintain performance to support business growth

• Entity Matching and Deduplication: Identify and merge duplicate records to maintain a single version of truth so that data stay accurate and consistent in records in a data mesh

• Data Hierarchy and Relationships Management: Manage the relationships and hierarchies between different data entities to give a clear understanding of data relationships

• Data Governance and Workflows: Implement policies, procedures, and workflows to manage data access and compliance as per industrial regulatory standards

• Data Quality Management: Provide tools and processes to monitor data quality and maintain it according to business requirements

  Data Syndication and Integration: Distribute and integrate master data across various systems and applications to improve collaboration and operational efficiency

• Data Storage and Management: Store and manage large volumes of structured and unstructured data

• Data Partitioning and Compression: Divind data into manageable segments and reduce data size without losing information

• Security and Access Control: Manage user access rights to avoid risks of unauthorized access or data breach.

• Scalability and Elasticity: Scale storage and compute resources up or down based on business demand

• Integration with BI and Analytics Tools: Connect seamlessly with business intelligence (BI) and analytics tools

• Metadata Management: Organize and manage metadata to provide proper context and information about data assets

• Data Discovery: Search for and find relevant data assets within the organization 

• Data Lineage: Track data’s lineage and transformations throughout its lifecycle 

• Data Classification: Categorize data based on its sensitivity or other criteria to help manage data according to its importance and regulatory requirements

• Integration: Connect and integrate with other data management and analytics tools

• Policy Management: Define and enforce data usage policies

• Data Lineage: Tracks data's origins and transformations

• Metadata Management: Organizes metadata to ease data discovery 

• Access Control: Manages who can access and modify data

• Compliance Management: Implements adherence to data regulations and standards

• Data Exploration and Querying: Enable users to explore and query data for in-depth analysis 

• Data Visualization Capabilities: Provide tools to create visual representations of data 

• Interactive Visualizations: Provide dynamic visualizations that users can interact with

• Self-Service Analytics: Empower users to analyze data independently without using outside help

• Data Sharing and Collaboration: Allow the sharing of data and insights among team members 

Need to understand all the tools teams are using to manage data? Use this data tech stack audit and survey template to get started.

See why data.world is your #1 data management tool

Data.world is the enterprise data catalog that scales modern data management through AI-driven data discovery and advanced data governance.

It democratizes data access with a user-friendly, chat-like interface. It's also a truly cloud-native SaaS platform that continuously updates according to enterprise requirements, and comes with no hidden costs.

Schedule a personalized demo and see how data.world can work magic for your data management strategy.