Best Data Management Software for Azure Data Lake Storage

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.

Azure Synapse is the Azure SQL Data Warehouse. Azure Synapse, a limitless analytics platform that combines enterprise data warehouse and Big Data analytics, is called Azure Synapse. It allows you to query data at your own pace, with either serverless or provisioned resources - at scale. Azure Synapse combines these two worlds with a single experience to ingest and prepare, manage and serve data for machine learning and BI needs.

IBM® StreamSets allows users to create and maintain smart streaming data pipelines using an intuitive graphical user interface. This facilitates seamless data integration in hybrid and multicloud environments. IBM StreamSets is used by leading global companies to support millions data pipelines, for modern analytics and intelligent applications. Reduce data staleness, and enable real-time information at scale. Handle millions of records across thousands of pipelines in seconds. Drag-and-drop processors that automatically detect and adapt to data drift will protect your data pipelines against unexpected changes and shifts. Create streaming pipelines for ingesting structured, semistructured, or unstructured data to deliver it to multiple destinations.

Progress DataDirect is passionate about empowering applications with enterprise data. We offer cloud and on-premises connectivity solutions for relational, NoSQL and Big Data data sources. We design solutions for thousands of companies and top vendors in analytics, data management, and BI. Our high-value connectors are designed to reduce development costs for a variety data sources. For greater security and peace of mind, you can get 24/7 support from experts around the world. For faster SQL access, connect with easy-to-use and time-saving drivers. Our mission is to keep up with the changing trends in data connectivity. If we don't have the connector you need, we will help you design it. Integrate connectivity into an application or service.

You can share data with other organizations in any format and size. You can easily control what data you share, who gets it, and the terms of your use. Data Share gives you full visibility into all data-sharing relationships through a user-friendly interface. You can share data with just a few clicks or create your own application using REST API. Serverless code-free data sharing service that doesn't require infrastructure setup or management. An intuitive interface to manage all data-sharing relationships. Automated data sharing for predictability and productivity. Secure data-sharing service that utilizes underlying Azure security measures. In just a few clicks, you can share structured and unstructured data from multiple Azure storages with other organizations. There is no infrastructure to create or manage, no SAS keys required, and sharing data is completely code-free. You can control data access and set terms that are consistent with your enterprise policies.

Integrate your data sources including relational and NoSQL database, SaaS and APIs. You can query them immediately as a single source of data. Process data wherever you are. Data from different sources can be merged, retrieved, and cached. Use webhooks for streaming data from Kafka or Segment into the Peaka Table. Real-time data access replaces nightly batch ingestion. Treat each data source as a relational database. Convert any API into a table and combine and join it with other data sources. Use familiar SQL to run queries on NoSQL databases. The same skills can be used to retrieve data from SQL and NoSQL database. You can query and filter your consolidated datasets to create new data sets. Use APIs to expose them and serve other apps or systems. Don't get bogged down with scripts and logs when setting up your data stack. Eliminate the burdens of managing and maintaining ETL pipelines.

Azure Data Lake offers all the capabilities needed to make it easy to store and analyze data across all platforms and languages. It eliminates the complexity of ingesting, storing, and streaming data, making it easier to get up-and-running with interactive, batch, and streaming analytics. Azure Data Lake integrates with existing IT investments to simplify data management and governance. It can also seamlessly integrate with existing IT investments such as data warehouses and operational stores, allowing you to extend your current data applications. We have the experience of working with enterprise customers, running large-scale processing and analytics for Microsoft businesses such as Office 365, Microsoft Windows, Bing, Azure, Windows, Windows, and Microsoft Windows. Azure Data Lake solves many productivity and scaling issues that prevent you from maximizing the potential of your data.

Run popular open-source frameworks--including Apache Hadoop, Spark, Hive, Kafka, and more--using Azure HDInsight, a customizable, enterprise-grade service for open-source analytics. You can process huge amounts of data quickly and enjoy all the benefits of the large open-source project community with the global scale Azure. You can easily migrate your big data workloads to the cloud. Open-source projects, clusters and other software are easy to set up and manage quickly. Big data clusters can reduce costs by using autoscaling and pricing levels that allow you only to use what you use. Data protection is assured by enterprise-grade security and industry-leading compliance, with over 30 certifications. Optimized components for open source technologies like Hadoop and Spark keep your up-to-date.

Azure Databricks allows you to unlock insights from all your data, build artificial intelligence (AI), solutions, and autoscale your Apache Spark™. You can also collaborate on shared projects with other people in an interactive workspace. Azure Databricks supports Python and Scala, R and Java, as well data science frameworks such as TensorFlow, PyTorch and scikit-learn. Azure Databricks offers the latest version of Apache Spark and allows seamless integration with open-source libraries. You can quickly spin up clusters and build in an Apache Spark environment that is fully managed and available worldwide. Clusters can be set up, configured, fine-tuned, and monitored to ensure performance and reliability. To reduce total cost of ownership (TCO), take advantage of autoscaling or auto-termination.

Data-driven organizations are constantly striving to become more data-driven. They build dashboards, analytics and data pipelines throughout the modern data stack. Unfortunately, data reliability issues are a major problem for most organizations, leading to poor decisions and a lack of trust in the data as an organisation, which directly impacts their bottom line. Resolving complex issues is a time-consuming and manual process that involves multiple teams, all of whom rely on tribal knowledge. They manually reverse-engineer complex data pipelines across various platforms to identify the root-cause and to understand the impact. Pantomath, a data pipeline traceability and observability platform, automates data operations. It continuously monitors datasets across the enterprise data ecosystem, providing context to complex data pipes by creating automated cross platform technical pipeline lineage.

As a leader in business, you must be able to trust your data, and be 100 percent certain that they are accurate, well-governed and compliant. Include all data from all sources and all locations without limitation. Understanding your data assets. Audit your project for quality, compliance and risk. Catalogue a complete inventory of data across all data types and sources, creating a shared understanding about your data assets. Conduct a fast, accurate, and affordable audit of your data. PCI, PII and PHI audits can be completed quickly, accurately and completely. No software to buy, as a service. Measure and audit the data quality and duplication of data across all your enterprise data assets - cloud-native or on-premises. Ensure compliance with global data privacy laws at scale. Discover, classify and audit privacy compliance. Monitor PII/PCI/PHI and automate DSAR processes.

Salesforce Data Cloud is an online data platform that allows businesses to collect, harmonize, and analyze data in real time. This creates a 360-degree customer profile which can be used across Salesforce's various applications, such as Marketing Cloud, Sales Cloud, and Service Cloud. It allows businesses collect, harmonize and analyze data in real-time, creating a 360° customer profile that can then be used across Salesforce's different applications, including Marketing Cloud, Sales Cloud and Service Cloud. This platform allows for faster, more personal customer interactions through the integration of data from online and off-line channels, such as CRM data, transactional information, and third-party sources. Salesforce Data Cloud offers advanced AI and analytics capabilities that help organizations gain deeper insight into customer behavior, and predict future needs. Salesforce Data Cloud helps improve customer experiences, target marketing, and data-driven decision making across departments by centralizing and refining the data.