Table of Contents Hide
- What is Data Management Software (DMS)?
- A-Z of Data Management Software In 2022
- #1. 1010data
- #2. Amazon Web Services (AWS)
- #3. Ataccama
- #4. Cloudera
- #5. Collibra
- #6. Commvault
- #7. Druva
- #8. Google
- #9. Hewlett-Packard Enterprise (HPE)
- #10. Hitachi Vantara
- #11. IBM
- #12. Immuta
- #13. Informatica
- #14. MarkLogic
- #15. Microsoft
- #16. Oracle
- #17. Precisely
- #18. Riversand
- #19. SAP
- #20. SAS
- #21. SingleStore
- #22. Snowflake
- #23. System Stibo
- #24. Talend
- #25. Tamr
- #26. Teradata
- #27. TIBCO
- #28. Zaloni
- What are the Features of Data Management Software?
- How to Select the Best Data Management Software
- Data Management Software FAQs
- What are the 4 types of data management systems?
- Why do we need data management software?
- What are data management skills?
Choosing the proper vendor and solution can be a difficult process that necessitates extensive research and typically involves more than simply the solution and its technical capabilities. We’ve profiled the best data management software companies for your small business in one spot to make your search a little easier. We’ve also included platform and product line names, as well as introductory software tutorials, so you can see each solution in action.
What is Data Management Software (DMS)?
Data management software (DMS) is software that collects data and turns it into a single storage container, or integrates disparate data into a consistent resource, such as a database. At various times, the specific phrase is used interchangeably with the larger term data management software, as many data management resources may direct incoming data to a database or set of databases.
A-Z of Data Management Software In 2022
1010data offers integrated database management and data analytics capabilities. 1010edge, the company’s flagship product, also supports data modeling and visualization, reporting, and application development. The technology grows to any size and combines diverse data together to deliver a granular perspective. Furthermore, the columnar data storage capabilities of the tool present data in an ordered manner.
#2. Amazon Web Services (AWS)
AWS provides Amazon Redshift, a fully managed, petabyte-scale data warehouse that analyzes data using an organization’s existing analytic software. The data warehouse architecture of Redshift enables users to automate basic administrative operations connected with cloud data warehousing provisioning, configuration, and monitoring. Continuous, incremental, and automatic backups to Amazon S3 are performed. Redshift Spectrum, which allows customers to conduct SQL queries against massive volumes of unstructured data without altering it, is also included.
Ataccama ONE is a complete master data management product with an exciting set of capabilities for a wide range of use cases. The management software includes a machine learning-centric user interface as well as a data processing engine that handles data transformations, business rule evaluation, and matching and merging rules. The platform supports any type of data, domain, and integration.
Cloudera offers an Apache Hadoop-based data storage and processing platform, as well as proprietary system and data management tools for design, implementation, operations, and production management. In October 2018, Cloudera acquired Hortonworks. Last September, it acquired San Mateo-based big data analytics specialist Arcadia Data. Cloudera’s new integrated data management product (Cloudera Data Platform) enables hybrid and multi-cloud analytics.
Collibra’s Data Dictionary documents an organization’s technical metadata as well as how it is used. It explains a piece of data’s structure, its relationship to other data, as well as its origin, format, and use. The solution acts as a searchable repository for users who need to know where and how data is kept, as well as how it can be used. Users can also define and map data using workflows and establish roles and responsibilities. Collibra data management software is unusual in that it was designed with business end-users in mind.
Commvault is well-known in the backup and disaster recovery sector as one of the leading solution suppliers. The company also provides a cloud data management product that enables businesses to manage data through on-premises and cloud deployments. Users have complete data management capabilities across files, applications, databases, hypervisors, and clouds (including Amazon Web Services, Microsoft Azure, Google Cloud, and Oracle Cloud). The product also features Commvault’s popular backup and disaster recovery capabilities, as well as e-discovery.
Druva Phoenix provides data availability and governance capabilities for virtual machines and physical servers. Its innovative cloud-centric strategy combines high-performance, scalable backup, disaster recovery, archive, and analytics. The product may be swiftly installed at facilities around the world while still complying with regional data storage rules. Phoenix can also be administered centrally, giving you complete control over server backups and data composition.
Google’s BigQuery product provides a fully managed enterprise data warehouse for analytics. The serverless solution allows enterprises to analyze any data by constructing a logical data warehouse using controlled, columnar storage, as well as data from object storage and spreadsheets. BigQuery is built on the Google Cloud Platform and gathers data in real-time via a streaming ingestion capability. The product also allows users to share insights through datasets, queries, spreadsheets, and reports.
#9. Hewlett-Packard Enterprise (HPE)
Hewlett Packard Enterprise (HPE) is the enterprise software division of the computer hardware behemoth HP. The provider provides a cloud-based database management system that may be accessed via Amazon Web Services, Microsoft Azure, or an individual licensed approach. Vertica provides an MPP SQL analytical database with native high availability and linear scaling, allowing enterprises to query data in near real-time.
#10. Hitachi Vantara
Hitachi Vantara is a wholly owned subsidiary of Hitachi, Ltd. that provides a diverse spectrum of products for data integration, management, and analysis. Hitachi’s data management software portfolio is best suited for current environments and may assist enterprises in rapidly improving critical performance metrics such as business continuity, backup windows, operational recovery, and disaster recovery. In addition, the product offers data protection and recovery for complicated organizational architectures.
IBM has data management products for almost every enterprise use case. Its technologies may be deployed in any environment, and collaborations with some of the industry’s biggest brands make it an even more appealing alternative for enterprises with massive workloads and extensive data jobs. IBM also provides the Informix database, which supports SQL, NoSQL/JSON, time series, and spatial data.
Immuta’s automated data governance technology allows users to discover and access data via a dedicated data catalog. The product has an intuitive policy builder that allows security executives to design policies in plain English rather than code, allowing them to apply to any data. Immuta also allows for compliance collaboration through projects, which are controlled workplaces where users can share data. Users assume the appropriate access and controls when they move projects.
Informatica’s big data management platform enables businesses to access, integrate, clean, master, govern, and secure big data. The application has custom interfaces to hundreds of data sources, real-time streaming, and mass ingestion. The visual developer interface of Informatica also ensures that the best open-source platforms may be used without sacrificing usability. AWS and Microsoft Azure provide public cloud capabilities for Big Data Management.
MarkLogic provides an operational and transactional enterprise NoSQL database that is intended for data integration, storage, management, and search. A flexible data architecture that responds to changing data allows organizations to consume structured and unstructured data. It can also store JSON, XML, text, and geographical data natively. Users may search across all data with MarkLogic’s Universal Index, and APIs enable application development and deployment. ACID transactions, scalability and flexibility, and proven security are all features of the database.
Microsoft provides a wide range of data management products, including analytics, data governance, and even data virtualization. Its SQL Server solution includes on-premises and cloud data warehousing, as well as an in-memory database. Microsoft enables businesses to access, store, and analyze any type of data and even provides fully managed Hadoop and Spark. With top-ranked solutions in business intelligence and data integration, the organization is one of the leading players in the overall big data marketplace.
Oracle’s data management capabilities enable users to handle both old and novel data types on the cloud platform. In addition, the company provides an autonomous data warehousing cloud with over 2,000 SaaS apps. The platform supports a wide range of big data features, including data integration and analytics. Oracle Big Data Cloud, Oracle Big Data Cloud Service, Oracle Big Data SQL Cloud Service, and Oracle NoSQL Database are among its other data management services.
Precisely’s solution portfolio is divided into five major areas based on use scenario. Precisely Connect, Ironstream, Assure, and Syncsort are part of its Integrate data integration portfolio. Precisely Spectrum Quality, Spectrum Context, and Trillium are all part of the Verify unit of data quality tools. The Precisely Spectrum Spatial, Spectrum Geocoding, and MapInfo are highlights of the Location Intelligence Suite (Locate), while Precisely Streets, Boundaries, Points Of Interest, Addresses, and Demographics are highlights of Enrich. On the company’s Engage unit, there’s also Precisely Engage.
Riversand is a provider of master data management (MDM) and product information management solutions. The MDM service from the company includes a multi-domain core designed to provide a comprehensive view of enterprise data. Riversand also features high-performance computing, a suite of streamlined collaboration tools, and data governance capability. Each license includes reporting via the vendor’s data visualization product, which allows customers to do advanced analysis via charts, tables, and dashboards.
SAP provides data management capabilities on a single platform. HANA SAP enables users to acquire and mix various forms of data in real-time, while also improving data governance, monitoring, and orchestration. Smart data integration, which enables enhanced applications and data management, also allows users to establish a unified picture of data. The platform is adaptable and can be installed on-premises, in the cloud, or in a hybrid configuration. HANA is an in-memory data processing and advanced analytics technology that supports OLAP and OLTP processing.
SAS is the world’s largest independent vendor in the data management business. The primary product of the company is founded on a data quality platform that allows customers to improve, integrate, and regulate enterprise data. SAS Data Management can import data from legacy systems and Hadoop, as well as construct and reuse rules. Users can also update data, tweak processes, and analyze results themselves. Collaboration is enabled through an integrated business lexicon, as well as third-party metadata management and lineage visualization tools.
SingleStore can ingest and transform millions of events every day, as well as analyze billions of rows of data with ordinary SQL. It can be deployed on-premises, in the cloud via Amazon Web Services or Microsoft Azure, or as a service with drop-in compatibility with existing middleware, integration, and business intelligence software. The tool now supports more effective query isolation for huge volumes of data and multiple users, in addition to outstanding real-time data streaming capabilities.
Snowflake provides a cloud data warehouse built on Amazon Web Services. The system loads and optimizes data from almost any structured or unstructured source, including JSON, Avro, and XML. Snowflake has extensive support for normal SQL, allowing users to perform updates, deletes, analytical functions, transactions, and sophisticated joins. The tool requires no management and no infrastructure. To crunch data, create reports, and execute analytics, the columnar database engine employs innovative optimizations.
#23. System Stibo
The Stibo Trailblazer Enterprise Platform (STEP) has data quality capabilities for data profiling, data matching, and enrichment with external reference data. The data management software also has an easy-to-use interface for implementing business rules, checks, and controls. The graphical interface validates duplication and matching with other inputs.
Talend provides a comprehensive suite of data integration and data management solutions. The Talend Data Management Platform, the company’s main data management product, includes graphical tools and wizards, as well as over 900 pre-built components and connectors for natively connecting databases, flat files, and cloud-based applications. Users can map complex EBCDIC files, XML, JSON, and EDI documents using the bundled data mapper and parsing capabilities.
Tamr is a popular data mastering platform that delivers analytic insights, increases operational efficiency, and improves data operations. Through machine learning, which consolidates, purifies, and categorizes data, the vendor’s cloud-native solutions serve as a viable alternative to traditional MDM products. Tamr’s Master Records function provides a comprehensive overview of all entities with simple yes/no queries. Tamr, which is supported by NEA and Google Ventures, offers the foundation for modern DataOps in a variety of industry verticals.
Teradata provides a wide range of data management solutions, including database management, cloud data warehousing, and data warehouse appliances. The product portfolio is accessible on the company’s own managed cloud, as well as Amazon Web Services and Microsoft Azure. Teradata enables enterprises to conduct a wide range of queries, in-database analytics, and complicated workload management.
The TIBCO boasts an amazing variety of data management products under its TIBCO Unify product line. TIBCO DQ (for data quality), TIBCO EBX (for master data management), and TIBCO Data Virtualization comprise the Unify suite. To automate manual procedures, TIBCO’s data management capabilities are infused with AI and machine learning. The company has grown its line of big data products through in-house development as well as acquisitions. TIBCO is also a market leader in BI and data analytics.
The Zaloni Data Management Platform operationalizes data along the pipeline, from data source to consumer. ZDP automates repeatable data management operations and processes and enables centralized management of all enterprise data sources, whether on-premises, in the cloud, across several clouds, or in a hybrid environment. Zaloni is compatible with all major Hadoop distributions, as well as the majority of data processing engines and deployment types.
What are the Features of Data Management Software?
Here are some of the key characteristics of data management tools that assist in identifying and correcting data inconsistencies and errors, making changes, and doing meaningful data analysis.
#1. Data Accuracy
Data management solutions can assist in identifying and filling gaps in missing information, as well as reducing redundancy, which would otherwise impair analytical precision.
#2. Data Management
Control over data is provided by such software tools, allowing you to immediately detect when and how data has been altered. It also allows you to create alerts so that you are aware of any changes as soon as they occur.
#3. Data Safety
You can safeguard access to your corporate data and prevent it from being breached by utilizing data storage management software capabilities such as tokenization, encryption, and access control.
#4. Management of Risk
To limit data risks, these solutions enable an organization to use controlled methods for accessing, integrating, and storing data across the data journey.
#5. Workflow Automation
You may automate repetitive processes in a workflow and optimize the data management process by using trigger-based features such as job scheduling.
How to Select the Best Data Management Software
Here are some factors to consider when selecting the best data management software for your companies:
#1. Assistance with Data Cleaning
A data management system should help you clean and correct data by resolving any quality issues, enhancing consistency, and removing redundancy. These tasks can be aided by transformations such as data profiling, data quality criteria, and data cleansing.
#2. Data Consolidation Function
A data management tool is required for an organization because of its capacity to integrate data from multiple source systems into a single central repository. It should enable automated and seamless data collecting from disparate systems and data formats (such as PDF, COBOL, delimited, etc.).
#3. Friendly User Interface
A data management solution should have an easy-to-use and intuitive interface so that even non-technical employees can utilize it when necessary. It should also give a single interface for managing all of your data. You should be able to recognize personal data and classify numerous data kinds from a single platform.
#4. Integration of Diverse Data Sources
To simplify data management, a data management application solution should allow for easy connectivity with other tools and software, such as Salesforce. Furthermore, it should enable team collaboration so that your business users may change processes, review results, and update data themselves.
#5. Features and Functionalities Scalability
As a business grows, so does the amount of data that must be managed and evaluated. As a result, scalable features and functions in data management application software should give you the flexibility to quickly handle your evolving business needs.
#6. Backup, recovery, and downtime of data
A data mart management software should include data backup and disaster recovery tools, allowing you to readily access and retrieve data in the event of a breakdown or other unforeseen occurrence. Furthermore, you should be able to readily edit data or perform routine upgrades with minimal disturbance or downtime.
#7. Total Ownership Cost
The cost of good data management software for your business is a significant consideration when selecting it. Several data storage management software options are available on the market, with some offering free trials.
We’ve just provided you with a summary of some of the most effective data management software companies All of these solutions are jam-packed with capabilities that can not only assist you to manage your data but also improve your overall working efficiency.
When choosing your choice, make sure it meets your needs, fits your preferences, and is within your budget. With powerful data management software at your disposal, you will be ready to conquer the business world without fear.
Data Management Software FAQs
What are the 4 types of data management systems?
- Customer Relationship Management System.
- Marketing technology systems.
- Data Warehouse systems.
- Analytics tools.
Why do we need data management software?
Data management reduces potential errors by establishing processes and regulations for usage and fostering trust in the data used to make decisions within your organization. Companies that have trustworthy, up-to-date data may adapt to market changes and customer needs more efficiently.
What are data management skills?
Data management skills are the abilities you employ to manage and utilize information successfully. Data management abilities include the ability to spot trends, comprehend database design concepts, and engage in short and long-term database project planning.
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