Data management tools boast functions like archiving, backup, disaster and recovery, archival, search, analytics, and more. While giants like Amazon and Google have dominated this niche, many smaller companies have entered the market to offer tools for customers with data needs of all sizes.
Data management isn't straightforward. It demands careful supervision from the moment the data is created until it's retired. When data is managed properly, you can mitigate risk while enhancing data usability and quality.
Companies often run into problems when working with data from disparate sources and scaling. Whether it's issues related to data duplication, isolation, or complex management issues, a robust data management strategy that is supported by the right tools can get you over any potential hurdle that lies ahead.
At its most basic level, data management (DM) describes the process of collecting, storing, and using data efficiently, securely, and cost-effectively. The primary objective here is to connect and pipe in data from different sources and make critical business decisions. However, as we generate more and more data in every aspect of our lives, DM can become increasingly challenging.
Effective data management is a combination of best practices, concepts, processes, procedures, and an extensive collection of tools that help enterprises control and manage their data resources effectively. In other words, it's a multiplatform heterogeneous process that involves various tools and objectives to achieve centralized data coherence. It's a process that is followed throughout the lifecycle of any data asset.
Tools essential to effective data management fall into these general categories:
We put together a list of the best data management tools from across these categories, which we've shared below. Keep in mind these aren't our rankings, instead, we've grouped tools to help you understand each category and to move closer to selecting the best data management tool for your needs.
Cloud data management tools help organizations integrate and manage data across multi-cloud environments. This approach allows companies with large volumes of data to store, sift through, analyze, and routinely manage their data entirely in the cloud.
Panoply is an ELT tool and a cloud-native data warehouse that makes data integration and management effortless. It is highly user-friendly and accommodates teams with varying skill sets, including business users.
Key features include:
TL;DR: it's an excellent turn-key business intelligence solution for SMBs who want to derive the most value from their data at a fraction of the cost.
Panoply price: a free trial is available; see all pricing options.
Amazon Web Services (AWS) offers an ever-expanding set of tools you can put together into an effective cloud data management stack. If you're already on AWS and are generating massive amounts of data, this might be the right cloud data management tool for you.
Key services include:
TL;DR: it's a useful tool for large enterprises that generate oceans of data and have the technical prowess to manage it. However, costs can quickly add up, so careful planning is necessary.
AWS price: varies and depends on your implementation.
Microsoft Azure offers a variety of options when it comes to setting up a cloud-based data management system. It also comes with various analytics tools that can be used on your Azure-stored data. Like AWS, Azure also accommodates multiple databases or data warehouse styles and provides a great set of tools for managing them.
Key services include:
TL;DR: as these tools are cloud-based, you're good to go without any implementation headaches. However, there's a learning curve if you're not familiar with the Azure environment.
Azure price: varies and depends on your implementation.
Like Amazon and Azure, the Google Cloud Platform also offers a wide array of cloud-based data management tools. It also provides a useful workflow manager that's leveraged to tie up different components together.
Key Google Cloud components include:
TL;DR: if you're already on Google Cloud and are working with vast amounts of data, this would be an easy addition, but even highly technical users will have to contend with a steep learning curve.
Google Cloud price: varies and depends on your implementation.
ETL and data integration tools move data from a source to a destination. If Different tools offer different degrees of flexibility in managing the extract-transform-load process (e.g., ETL vs. ELT), so be mindful of your business needs when vetting them.
Modern ETL tools also vary widely in terms of how you can work with your data. Some tools offer visual interfaces, others provide point-and-click integration, while still others require a more robust knowledge of code.
Informatica PowerCenter is an on-premise ETL tool. Informatica PowerCenter offers the following key features:
TL;DR: In a world of cloud platforms, Informatica PowerCenter is an on-prem holdout that could be exactly what companies bound by complex regulatory concerns need.
Informatica PowerCenter price: available upon request.
Stitch Data is a cloud-based ETL platform. Stitch offers the following key features:
TL;DR: Stitch offers a wide array of integrations as well as a number of community-sourced connectors via its open source Segment platform, making it a highly popular choice.
Stitch price: starts at $100/month, based on data size
Fivetran is a fully-managed data pipeline with a web interface that integrates data from SaaS services and databases into a single data warehouse. Fivetran's key features include:
Provides direct integration and sends data over a direct secure connection using a sophisticated caching layer
Caching layer helps to move data from one point to another without ever storing a copy on the application server
Fivetran does not impose any data limit
Can be used to centralize a company’s data and integrate all sources to determine Key Performance Indicators (KPIs) across an entire organization
TL;DR: Fivetran is big and only likely to get bigger given its recent valuation. It's known for being a bit more complex than Stitch, but the real make-or-break is whether or not it has the connectors you need.
Fivetran price: Starts at $1/credit; the pricing model is based on Monthly Active Rows.
Blendo is another cloud-based ETL and data integration service, with the following key features:
TL;DR: Often praised for its service, Blendo is a solid choice but may lack some critical integrations.
Blendo price: starts at $150/month, depends on the number and types of integrations as well as data volume.
Microsoft offers SSIS, a graphical interface for managing ETL using MS SQL Server. Key features include:
TL;DR: If you're working with SQL Server, SSIS is an obvious option. However, it does require coding skills for some operations, which could be a problem for less technical teams.
SSIS price: $0.450/hour
In addition to SQL Server SSIS, Microsoft’s on-premise ETL solution, the company also offers Azure Data Factory (ADF), an ETL tool for their cloud-based Azure platform. Key features of ADF:
TL;DR: Azure Data Factory is a more user-friendly option than SQL Server SSIS that could be ideal for companies looking for an on-premise ETL option.
Azure Data Factory price: $1 for 1,000 runs.
Talend open source data integration software products provide software to integrate, cleanse, mask and profile data. Key features of Talend offerings include:
TL;DR: Tons of reliable connectors make Talend a favorite among its users, but it does require some expertise to manage well.
Talend price: $1,170/user monthly or $12,000 annually.
Alooma offers an enterprise-scale data integration platform with great ETL tools built in. Some key features of Alooma offerings:
TL;DR: If you've got massive amounts of data, Alooma could be a good option. However, user complaints about difficult debugging could be a dealbreaker.
Alooma price: available upon request.
Data transformation tools enable businesses to change data formats through automation. It's a critical step in the data integration process where both structured and unstructured data from disparate sources are migrated and automatically transformed within minutes.
It's crucial because any misstep could lead to incompatibility and data loss. So when choosing a data transformation tool, it's essential to pick one that offers transformation, cleansing, and enrichment without data loss.
Dataform enables collaboration on SQL pipelines in BigQuery. This fully managed data transformation platform helps organizations effectively handle different cloud data warehouse processes.
Key features include:
TL;DR: Dataform is best suited for medium to large enterprises with a team of data analysts and engineers. As it's a highly technical tool, it's not an option for business users.
Dataform price: varies and depends on the number of users and features used. A free version is available.
dbt (data build tool) is a SQL-based data transformation tool that initiates data transformation by writing SELECT
statements. Built to streamline data analytics and engineering workflows, you have to write models that reflect your core business logic.
Key features include:
TL;DR: it's open-source and highly customizable. It's SQL-based and only the "T" in ETL, so you'll need other tools to work with it.
DBT price: $50 per developer seat, per month, or custom pricing for enterprise teams, and a free basic tier for developers is also available.
Airflow is a popular open-source data infrastructure tool originally developed at Airbnb. Although it doesn't actually do any data processing, Airflow helps schedule, organize, and monitor ETL processes using Python.
Key features include:
TL;DR: if you already have a team of Python coders on hand, you're good to go. The CI/CD can be tricky, and there's no native support for Windows.
Airflow price: is free and open source.
Like Airflow, Luigi is also an open-source solution, but Spotify developed it. This Python-based tool makes the management of long-running batch processes easier. It can handle tasks that go far beyond the scope of ETL, but it does ETL pretty well too.
Key features include:
TL;DR: it's a good option for enterprises with Python coders, but unlike Airflow, not much development is going on right now in the Luigi ecosystem.
Luigi price: is free and open source.
Master Data Management (MDM) tools aim to manage the central and master data of a business. These include customer data, employee data, operations data, regulatory data, and more.
MDM tools help you with data cleansing, centralization, transaction control, key mapping, and multidomain support. You can also use these tools for information distribution and global synchronization across different locations.
Dell Boomi Master Data Hub is an enterprise-grade platform that leverages the cloud to maximum effect. Cohesive and versatile, it helps organizations effectively manage a variety of applications and data sources across hybrid cloud environments.
Key features include:
TL;DR: it's a tool that accommodates non-techy business users, but Boomi doesn't come cheap.
Dell Boomi Master Data Hub price: follows a customized pricing model, and a 30-day free trial is available.
Profisee Master Data Management helps enterprises manage master data by cleaning, standardizing, and matching source data. You can enforce business processes and empower data stewards to master data by leveraging feedback from analytics, including governance and progress measurements.
Key features include:
TL;DR: Profisee MDM comes with a user-friendly and intuitive UI, but you still have to contend with a learning curve. It's best suited for regulated industries like finance, healthcare, and insurance.
Profisee price: available upon request.
SAP NetWeaver MDM is a component of the NetWeaver development platform. It enables swift and flexible design, implementation, and execution of new business strategies and processes. If you're already working with SAP products like mySAP suite, it's relatively easy to integrate data about your people and processes.
Key features include:
TL;DR: it's a powerful solution that comes with many features. But you'll need to have the necessary skill sets to get the most out of this solution.
SAP NetWeaver pricing: available upon request.
The Semarchy xDM platform is a popular platform among leading brands in Europe and North America. Also known as Semarchy Intelligent MDM, the tool helps companies overcome data governance challenges. Companies can leverage xDM's material design, as well as AI and ML protocols for data enrichment, data quality, and data stewardship.
Key features include:
TL;DR: it's a reliable solution leveraged by large enterprises to overcome data governance challenges. However, you'll need some skills and experience to use it.
Semarchy xDM price: available upon request.
TIBCO is a leading MDM solution that's popular among industries like banking, energy, insurance, government agencies, and more. It's an excellent tool for companies that require multidomain management, workflow visualization, relationship mapping, and more.
Key features include:
TL;DR: TIBCO MDM is best suited for large enterprises that want to manage different data types in a centralized location. It's not very intuitive and can be quite a challenge for beginners and new users.
Tibco MDM price: available upon request.
Ataccama ONE is a highly automated data management and governance tool that can be run on-premise, in the cloud, or in a hybrid setup. This AI-powered platform is ready for mission-critical deployments and integrates and unifies data governance, data quality, and master data management.
Key features include:
TL;DR: Acama ONE provides all your data management tools in one centralized location, but users report that it can be quite buggy with each update.
Ataccama ONE price: available upon request, and a free trial is available.
Stibo Systems is probably the oldest company on this list. Founded in 1795 in Denmark, Stibo has undoubtedly come a long way since its origins as a printing company. Stibo STEP is more of a recent addition to the company's data management arm. It provides a high level of automation, merging, and centralized data across channels like products, suppliers, customers, and location information.
STEP is popular among enterprises in industries like finance, manufacturing, travel, and hospitality. Furthermore, its automated data and language translation feature makes it highly suitable for multinational operations.
Key features include:
TL;DR: Stibo STEP is perfect for multinationals who require cross-channel consistency, but you'll need the necessary expertise to use it.
Stibo STEP price: available upon request.
Reference data management is a subset of master data management used for classification and defining permissible values used by other fields, both internally and externally. These can be anything from zip codes, country codes, measurement units, currency, products and pricing, and so on.
It's crucial to use robust tools to manage this type of data as it serves as a reference point for a number of systems. Poor reference data management can lead to operational inefficiencies, poor governance, and incorrect reporting and analytics.
Collibra's Data Governance offering comes with reference data tools that help analysts, data scientists, stewards, and business users by automating workflows to create new code sets. It also performs accurate data mapping to remove barriers to seamless data access.
Key features include:
TL;DR: feature-rich, but pricing can be confusing, and implementation costs can come as a surprise to some customers.
Collibra price: available upon request.
Magnitude Reference Data Management is equipped to integrate various domains into a single model and enables the support of cross-domain relationships. Smart algorithms help minimize manual stewardship through automated matching, harmonization, and survivorship.
Key features include:
TL;DR: Magnitude is a business user-friendly tool, but it can get complicated once you start integrating data from multiple sources.
Magnitude Reference Data Management price: available upon request.
Informatica MDM Reference 360 is a cloud-based tool that provides an end-to-end approach with embedded data quality, data integration, process management, and more. As it's fully-cloud-based, you can improve performance and scalability without much effort.
Key features include:
TL;DR: Informatica MDM Reference 360 helps users quickly implement rules and make changes, but there can be a steep learning curve.
Informatica MDM Reference 360 price: available upon request.
Reltio Cloud is a graph-based master data management tool that is equipped with reference data management tools. Reltio is built on graph databases to provide maximum flexibility in scaling data stores and defining clear relationships between the data in your repository.
Reltio can be used to manage mission-critical data and win in the experience economy. Reltio Connected Customer 360, built on cloud-native, big data architecture featuring graph technology and machine learning, is at the heart of customer experiences. This approach enables hyper-personalization, accelerated real-time operations, and simplifies compliance, and all at scale.
Key features include:
TL;DR: it's an excellent tool for Fortune 500 companies focused on delivering enhanced customer experiences, but you'll have to contend with a steep learning curve.
Reltio Cloud price: available upon request with a free trial option.
From machine learning-enabled notebooks to drag-and-drop dashboards, analytics and visualization tools are designed to help you derive insights from your data.
While all the options on this list offer some degree of data visualization, tools vary in the customizability of your data viz. These tools also offer a range of query options from SQL-first to drag-and-drop.
Tableau is a BI platform available both on the cloud and as downloadable software, with the following key features:
TL;DR: Tableau is great for businesses that are seriously into data viz but that also want the ease of drag-and-drop analysis.
Tableau price: starts at $70 per user per month.
TL;DR: Cumul.io is a top-notch option for companies looking to offer embedded analytics, especially if they want customer-facing dashboards up and running quickly.
Cumul.io price: $995 - $2,700 per month for full embedded capability or white-labeling, with plans ranging from 100-1000 monthly active viewers.
Looker is another cloud-based analytics and visualization platform, with the following key features:
TL;DR: Looker is ideal for companies that prefer downstream control of their data model and business logic.
Looker price: available upon request.
Metabase offers a user-friendly, open source interface for connecting and analyzing your data. As a data visualization tool, it offers:
TL;DR: Metabase's low cost can help companies get started with analytics and visualization, but may fall short as a long-term solution.
Metabase price: Metabase is free and open source, so its free tier offers a range of features that will be suitable for most users. Paid plans start at $100/month.
Power BI, Microsoft’s offering in the business analytics space, is designed to be useful for business analysts and data scientists alike. Main features:
TL;DR: Power BI is popular for a reason: it's easy to use thanks to its Excel-like interface that lowers the barrier to entry for non-analysts.
Microsoft Power BI price: $9.99 per user per month.
Mode Analytics offers a web-based data analytics suite aimed at data scientists and analysts, with a focus on collaboration and sharing. Some of Mode’s key features:
TL;DR: Mode is ideal for teams that need to support both analysts looking to use SQL, r, or Python and business users who need easy dashboarding.
Mode Analytics price: available upon request.
If you need an all-in-one tool, ClicData could be a good fit. Its primary features include:
TL;DR: ClicData could work well for companies that prefer to work with a single vendor for all their data needs. When evaluating cost, pay close attention to what pricing tier your data sources will land you in.
ClicData price: starts at $71 per month for an annual contract.
There's no replacement for managing business processes around structured data in large organizations, but cloud-based platforms can help with data management strategy. For example, they can support the treatment and preparation of raw data, data ingestion, loading, transformation, optimization, and visualization, all automatically in a single system.
For example, Panoply's cloud data platform can connect directly to data sources, manage data loading, and automatically transform your data into clean tables that are ready for analysis. Tools that provide an integrated big data stack take us one step closer to a truly holistic data management concept.
At Panoply, we believe in simple and robust data management. Although Panoply was developed to work well for data engineers who simply don't have the bandwidth to manage everything on their own, analysts can also be successful.