Best Data Management Software for Shapelets
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Compare the Top Data Management Software that integrates with Shapelets as of December 2025
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This a list of Data Management software that integrates with Shapelets. Use the filters on the left to add additional filters for products that have integrations with Shapelets. View the products that work with Shapelets in the table below.
What is Data Management Software for Shapelets?
Data management software systems are software platforms that help organize, store and analyze information. They provide a secure platform for data sharing and analysis with features such as reporting, automation, visualizations, and collaboration. Data management software can be customized to fit the needs of any organization by providing numerous user options to easily access or modify data. These systems enable organizations to keep track of their data more efficiently while reducing the risk of data loss or breaches for improved business security. Compare and read user reviews of the best Data Management software for Shapelets currently available using the table below. This list is updated regularly.
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1
MongoDB
MongoDB
MongoDB is a general purpose, document-based, distributed database built for modern application developers and for the cloud era. No database is more productive to use. Ship and iterate 3–5x faster with our flexible document data model and a unified query interface for any use case. Whether it’s your first customer or 20 million users around the world, meet your performance SLAs in any environment. Easily ensure high availability, protect data integrity, and meet the security and compliance standards for your mission-critical workloads. An integrated suite of cloud database services that allow you to address a wide variety of use cases, from transactional to analytical, from search to data visualizations. Launch secure mobile apps with native, edge-to-cloud sync and automatic conflict resolution. Run MongoDB anywhere, from your laptop to your data center.Starting Price: Free -
2
Tableau
Salesforce
Tableau, now enhanced with AI-powered capabilities and integrated with Salesforce, is an advanced analytics platform that helps businesses turn data into actionable insights. With Tableau Next, users can unlock the full potential of their data by accessing trusted AI-driven analytics. Whether deployed in the cloud, on-premises, or natively within Salesforce CRM, Tableau enables seamless data integration, powerful visualizations, and collaboration. The platform is designed to support organizations of all sizes in making data-driven decisions, while fostering a Data Culture through easy-to-use, intuitive tools for analysts, business leaders, IT leaders, and developers alike.Starting Price: $75/user/month -
3
Strategy ONE
Strategy Software
Strategy ONE (formerly MicroStrategy) is an AI-powered platform designed to accelerate business intelligence and data-driven insights. It combines advanced AI with business intelligence (BI) tools to help organizations streamline workflows, automate processes, and improve data accessibility. With its ability to integrate multiple data sources, Strategy ONE ensures that businesses can trust the data they analyze and make informed decisions faster. The platform supports cloud-native technologies, enabling seamless scalability and adaptability. Additionally, Strategy ONE’s AI chat interface allows for intuitive data querying and analysis, making it easier for users to interact with their data and drive impactful results. -
4
Apache Kafka
The Apache Software Foundation
Apache Kafka® is an open-source, distributed streaming platform. Scale production clusters up to a thousand brokers, trillions of messages per day, petabytes of data, hundreds of thousands of partitions. Elastically expand and contract storage and processing. Stretch clusters efficiently over availability zones or connect separate clusters across geographic regions. Process streams of events with joins, aggregations, filters, transformations, and more, using event-time and exactly-once processing. Kafka’s out-of-the-box Connect interface integrates with hundreds of event sources and event sinks including Postgres, JMS, Elasticsearch, AWS S3, and more. Read, write, and process streams of events in a vast array of programming languages. -
5
Spotfire
Cloud Software Group
Spotfire is the most complete analytics solution on the market, enabling everyone to explore and visualize new discoveries in data through immersive dashboards and advanced analytics. Spotfire analytics delivers capabilities at scale, including predictive analytics, geolocation analytics, and streaming analytics. And with Spotfire Mods, you can build tailored analytic apps rapidly, repeatedly, and to scale. With the Spotfire analytics platform you get a seamless, single-pane-of-glass experience for visual analytics, data discovery, and point-and-click insights. Immerse yourself in both historic and real-time data, interactively. Drill down or across multi-layer, disparate data sources with fully brush-linked, responsive visualizations. Imagine, then rapidly build, scalable tailored analytics apps using the Spotfire Mods framework, to get all the power of Spotfire software in your own fit-for-purpose analytics apps.Starting Price: $25 per month -
6
The Qlik Data Integration platform for managed data lakes automates the process of providing continuously updated, accurate, and trusted data sets for business analytics. Data engineers have the agility to quickly add new sources and ensure success at every step of the data lake pipeline from real-time data ingestion, to refinement, provisioning, and governance. A simple and universal solution for continually ingesting enterprise data into popular data lakes in real-time. A model-driven approach for quickly designing, building, and managing data lakes on-premises or in the cloud. Deliver a smart enterprise-scale data catalog to securely share all of your derived data sets with business users.
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7
Apache HBase
The Apache Software Foundation
Use Apache HBase™ when you need random, realtime read/write access to your Big Data. This project's goal is the hosting of very large tables -- billions of rows X millions of columns -- atop clusters of commodity hardware. Automatic failover support between RegionServers. Easy to use Java API for client access. Thrift gateway and a REST-ful Web service that supports XML, Protobuf, and binary data encoding options. Support for exporting metrics via the Hadoop metrics subsystem to files or Ganglia; or via JMX. -
8
SAS MDM
SAS
Integrate master data management technologies with those in SAS 9.4. SAS MDM is a web-based application that is accessed through the SAS Data Management Console. It provides a single, accurate and unified view of corporate data, integrating information from various data sources into one master record. SAS® Data Remediation and SAS® Task Manager work together with SAS MDM and as well as with other software offerings, such as SAS® Data Management and SAS® Data Quality. SAS Data Remediation enables users to manage and correct issues triggered by business rules in SAS MDM batch jobs and real-time processes. SAS Task Manager is a complementary application to others that integrate with SAS Workflow technologies giving users direct access to a workflow that might have been initiated from another SAS application. Users can start, stop, and transition workflows that have been uploaded to the SAS Workflow server environment. -
9
HPE Ezmeral Data Fabric
Hewlett Packard Enterprise
Access HPE Ezmeral Data Fabric Software as a fully managed service. Register now for a 300GB instance to try out the latest features and capabilities. Increasingly enterprise data is being distributed across a growing number of locations while at the same time, the demand for insights continues to grow as users expect richer, high-quality data insights. Hybrid cloud solutions offer the best outcomes in terms of cost, data placement, workload control, and user experience. The upside of hybrid is the ability to better match applications with the appropriate services across the application lifecycle. The downside of hybrid is that it adds a new dimension of complexity such as limited data visibility, the need to use multiple analytic formats, and the potential for organizational risk and increased costs.
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