Best Data Management Software for Hadoop

StarTree Cloud is a fully-managed real-time analytics platform designed for OLAP at massive speed and scale for user-facing applications. Powered by Apache Pinot, StarTree Cloud provides enterprise-grade reliability and advanced capabilities such as tiered storage, scalable upserts, plus additional indexes and connectors. It integrates seamlessly with transactional databases and event streaming platforms, ingesting data at millions of events per second and indexing it for lightning-fast query responses. StarTree Cloud is available on your favorite public cloud or for private SaaS deployment. StarTree Cloud includes StarTree Data Manager, which allows you to ingest data from both real-time sources such as Amazon Kinesis, Apache Kafka, Apache Pulsar, or Redpanda, as well as batch data sources such as data warehouses like Snowflake, Delta Lake or Google BigQuery, or object stores like Amazon S3, Apache Flink, Apache Hadoop, or Apache Spark. StarTree ThirdEye is an add-on anomaly detection system running on top of StarTree Cloud that observes your business-critical metrics, alerting you and allowing you to perform root-cause analysis — all in real-time.

ActiveBatch by Redwood is a centralized workload automation platform, that seamlessly connects and automates processes across critical systems like Informatica, SAP, Oracle, Microsoft and more. Use ActiveBatch's low-code Super REST API adapter, intuitive drag-and-drop workflow designer, over 100 pre-built job steps and connectors, available for on-premises, cloud or hybrid environments. Effortlessly manage your processes and maintain visibility with real-time monitoring and customizable alerts via emails or SMS to ensure SLAs are achieved. Experience unparalleled scalability with Managed Smart Queues, optimizing resources for high-volume workloads and reducing end-to-end process times. ActiveBatch holds ISO 27001 and SOC 2, Type II certifications, encrypted connections, and undergoes regular third-party tests. Benefit from continuous updates and unwavering support from our dedicated Customer Success team, providing 24x7 assistance and on-demand training to ensure your success.

Enhance your data warehouse (DWH) development process by leveraging automation to design and produce intricate data models, such as dimensional, data mart, and data vault frameworks. This automated approach significantly shortens the time to realize value by optimizing workflows, which leads to greater accuracy and consistency in your data. With AnalyticsCreator, you can easily connect your data to various platforms including MS Fabric, Power BI, Snowflake, Tableau, and Azure Synapse, among others. The tool features built-in transformations and historization functions that allow for effective management of historical data, including support for Slowly Changing Dimensions (SCD) types, thereby improving data governance and operational performance. Facilitate collaboration and streamline your team's efforts with advanced version control capabilities and automated documentation processes, which help minimize development time. This enables quicker prototyping, schema evolution, and effective metadata management, fostering a more responsive approach to data management.

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.

Scalytics Connect combines data mesh and in-situ data processing with polystore technology, resulting in increased data scalability, increased data processing speed, and multiplying data analytics capabilities without losing privacy or security. You take advantage of all your data without wasting time with data copy or movement, enable innovation with enhanced data analytics, generative AI and federated learning (FL) developments. Scalytics Connect enables any organization to directly apply data analytics, train machine learning (ML) or generative AI (LLM) models on their installed data architecture.

It takes only days to wrap any data source with a single reference Data API and simplify access to reporting and analytics data across your teams. Make it easy for application developers and data engineers to access the data from any source in a streamlined manner. - The single schema-less Data API endpoint - Review, configure metrics and dimensions in one place via UI - Data model visualization to make faster decisions - Data Export management scheduling API Our proxy perfectly fits into your current API management ecosystem (versioning, data access, discovery) no matter if you are using Mulesoft, Apigee, Tyk, or your homegrown solution. Leverage the capabilities of Data API and enrich your products with self-service analytics for dashboards, data Exports, or custom report composer for ad-hoc metric querying. Ready-to-use Report Builder and JavaScript components for popular charting libraries (Highcharts, BizCharts, Chart.js, etc.) makes it easy to embed data-rich functionality into your products. Your product or service users will love that because everybody likes to make data-driven decisions! And you will not have to make custom report queries anymore!

It shouldn't take long to analyze data from your business solutions. Zuar Runner allows you to automate your ELT/ETL processes, and have data flow from hundreds of sources into one destination. Zuar Runner can manage everything: transport, warehouse, transformation, model, reporting, and monitoring. Our experts will make sure your deployment goes smoothly and quickly.

MongoDB is a versatile, document-oriented, distributed database designed specifically for contemporary application developers and the cloud landscape. It offers unparalleled productivity, enabling teams to ship and iterate products 3 to 5 times faster thanks to its adaptable document data model and a single query interface that caters to diverse needs. Regardless of whether you're serving your very first customer or managing 20 million users globally, you'll be able to meet your performance service level agreements in any setting. The platform simplifies high availability, safeguards data integrity, and adheres to the security and compliance requirements for your critical workloads. Additionally, it features a comprehensive suite of cloud database services that support a broad array of use cases, including transactional processing, analytics, search functionality, and data visualizations. Furthermore, you can easily deploy secure mobile applications with built-in edge-to-cloud synchronization and automatic resolution of conflicts. MongoDB's flexibility allows you to operate it in various environments, from personal laptops to extensive data centers, making it a highly adaptable solution for modern data management challenges.

Kyvos is a semantic data lakehouse designed to speed up every BI and AI initiative, offering lightning-fast analytics at an infinite scale with maximum cost efficiency and the lowest possible carbon footprint. The platform provides high-performance storage for both structured and unstructured data, ensuring trusted data for AI applications. It is built to scale seamlessly, making it an ideal solution for enterprises aiming to maximize their data’s potential. Kyvos is infrastructure-agnostic, which means it fits perfectly into any modern data or AI stack, whether deployed on-premises or in the cloud. Leading companies rely on Kyvos as a unified source for cost-effective, high-performance analytics that foster deep, meaningful insights and context-aware AI application development. By leveraging Kyvos, organizations can break through data barriers, accelerate decision-making, and enhance their AI-driven initiatives. The platform's flexibility allows businesses to create a scalable foundation for a range of data-driven solutions.

The Jupyter Notebook is a web-based open-source tool that enables users to create and distribute documents featuring live code, visualizations, equations, and written explanations. Its applications are diverse and encompass tasks such as data cleaning and transformation, statistical modeling, numerical simulations, data visualization, machine learning, among others, showcasing its versatility in various fields. Additionally, it serves as an excellent platform for collaboration and sharing insights within the data science community.

Pentaho+ is an integrated suite of products that provides data integration, analytics and cataloging. It also optimizes and improves quality. This allows for seamless data management and drives innovation and informed decisions. Pentaho+ helped customers achieve 3x more improved data trust and 7x more impactful business results, as well as a 70% increase productivity.

When seeking a database that ensures both scalability and high availability without sacrificing performance, Apache Cassandra stands out as an ideal option. Its linear scalability paired with proven fault tolerance on standard hardware or cloud services positions it as an excellent choice for handling mission-critical data effectively. Additionally, Cassandra's superior capability to replicate data across several datacenters not only enhances user experience by reducing latency but also offers reassurance in the event of regional failures. This combination of features makes it a robust solution for organizations that prioritize data resilience and efficiency.

SingleStore, previously known as MemSQL, is a highly scalable and distributed SQL database that can operate in any environment. It is designed to provide exceptional performance for both transactional and analytical tasks while utilizing well-known relational models. This database supports continuous data ingestion, enabling operational analytics critical for frontline business activities. With the capacity to handle millions of events each second, SingleStore ensures ACID transactions and allows for the simultaneous analysis of vast amounts of data across various formats, including relational SQL, JSON, geospatial, and full-text search. It excels in data ingestion performance at scale and incorporates built-in batch loading alongside real-time data pipelines. Leveraging ANSI SQL, SingleStore offers rapid query responses for both current and historical data, facilitating ad hoc analysis through business intelligence tools. Additionally, it empowers users to execute machine learning algorithms for immediate scoring and conduct geoanalytic queries in real-time, thereby enhancing decision-making processes. Furthermore, its versatility makes it a strong choice for organizations looking to derive insights from diverse data types efficiently.

A platform for data management powered by AI that allows data democratization. Insights drives innovation by integrating and centralizing all data sources, facilitating collaboration, and empowering organizations for innovation. SCIKIQ, a holistic business platform, simplifies the data complexities of business users through a drag-and-drop user interface. This allows businesses to concentrate on driving value out of data, allowing them to grow and make better decisions. You can connect any data source and use box integration to ingest both structured and unstructured data. Built for business users, easy to use, no-code platform, drag and drop data management. Self-learning platform. Cloud agnostic, environment agnostic. You can build on top of any data environment. The SCIKIQ architecture was specifically designed to address the complex hybrid data landscape.

Trino is a remarkably fast query engine designed to operate at exceptional speeds. It serves as a high-performance, distributed SQL query engine tailored for big data analytics, enabling users to delve into their vast data environments. Constructed for optimal efficiency, Trino excels in low-latency analytics and is extensively utilized by some of the largest enterprises globally to perform queries on exabyte-scale data lakes and enormous data warehouses. It accommodates a variety of scenarios, including interactive ad-hoc analytics, extensive batch queries spanning several hours, and high-throughput applications that require rapid sub-second query responses. Trino adheres to ANSI SQL standards, making it compatible with popular business intelligence tools like R, Tableau, Power BI, and Superset. Moreover, it allows direct querying of data from various sources such as Hadoop, S3, Cassandra, and MySQL, eliminating the need for cumbersome, time-consuming, and error-prone data copying processes. This capability empowers users to access and analyze data from multiple systems seamlessly within a single query. Such versatility makes Trino a powerful asset in today's data-driven landscape.

Style Intelligence from InetSoft is a complete business intelligence platform that empowers companies with the ability to analyze, monitor, report and collaborate on business and operational data coming from different sources in real-time. Its top features include a data mashup Data Block architecture and professional atomic block modeling tool. There is also a database write-back option. Style Intelligence is robust and easy-to-use. It offers granular security, multitenancy support, multiple integrations, and is fully scalable.

DreamFactory is a REST API Management Platform. Auto Generate REST APIs. A cloud-based or on-premise API generation platform that is enterprise-grade. Instantly generate database APIs to build faster applications. The biggest bottleneck in modern IT is eliminated. Your project can be launched in weeks instead of months. DreamFactory creates a secure, standardized and reusable, fully documented, live REST API. DreamFactory can integrate any SQL or NoSQL file storage system or SOAP service. It instantly creates a RESTAPI with Swagger documentation, user role, and more. Every API endpoint is secured with User Management, Role Based Access Controls, SSO Authentication and Swagger documentation. Rapidly create mobile, web and IoT apps using REST-based APIs. DreamFactory offers example apps for iOS, Android and Titanium.

Toucan, a customer-facing platform for analytics, empowers organizations to drive engagement and provide the best possible end-user experience. Toucan makes it simple, from data connections to the distribution and sharing of insights wherever they are needed. Toucan analytics are 3x more popular than the industry average. With hundreds of connectors, users can connect to any cloud-based or stored data. Data readiness features make data preparation easy for business people. They can perform tasks that would normally require an expert. Visualization can be described as "data storytelling", where every chart is accompanied with context, collaboration and annotation to help users understand the "why" behind their data. Finally, deployment and management are easy with one-touch deployment, from staging to production, easy embedding and publishing to any device.

Bacula Enterprise offers a single platform that provides cloud backup and recovery software for the Modern Data Center. Bacula Enterprise backup & recovery software is ideal for medium and large businesses. It offers unique innovation, modern architecture and business value benefits, as well as low cost of ownership. Bacula Enterprise corporate backup software solution uses unique technologies that increase the interoperability of Bacula Enterprise into many IT environments, such as managed service providers, software vendors, cloud providers, enterprise data centers, and cloud providers. Bacula Enterprise is used by thousands of organizations around the world in mission-critical environments such as NASA, Texas A&M University and Unicredit. Bacula offers more security features than other vendors and advanced hybrid Cloud connectivity to Amazon S3, Google, Oracle, and many others.

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.

Enhance your metrics and alerting capabilities using a top-tier open-source monitoring tool. Prometheus inherently organizes all data as time series, which consist of sequences of timestamped values associated with the same metric and a specific set of labeled dimensions. In addition to the stored time series, Prometheus has the capability to create temporary derived time series based on query outcomes. The tool features a powerful query language known as PromQL (Prometheus Query Language), allowing users to select and aggregate time series data in real time. The output from an expression can be displayed as a graph, viewed in tabular format through Prometheus’s expression browser, or accessed by external systems through the HTTP API. Configuration of Prometheus is achieved through a combination of command-line flags and a configuration file, where the flags are used to set immutable system parameters like storage locations and retention limits for both disk and memory. This dual method of configuration ensures a flexible and tailored monitoring setup that can adapt to various user needs. For those interested in exploring this robust tool, further details can be found at: https://sourceforge.net/projects/prometheus.mirror/

IBM Analytics Engine offers a unique architecture for Hadoop clusters by separating the compute and storage components. Rather than relying on a fixed cluster with nodes that serve both purposes, this engine enables users to utilize an object storage layer, such as IBM Cloud Object Storage, and to dynamically create computing clusters as needed. This decoupling enhances the flexibility, scalability, and ease of maintenance of big data analytics platforms. Built on a stack that complies with ODPi and equipped with cutting-edge data science tools, it integrates seamlessly with the larger Apache Hadoop and Apache Spark ecosystems. Users can define clusters tailored to their specific application needs, selecting the suitable software package, version, and cluster size. They have the option to utilize the clusters for as long as necessary and terminate them immediately after job completion. Additionally, users can configure these clusters with third-party analytics libraries and packages, and leverage IBM Cloud services, including machine learning, to deploy their workloads effectively. This approach allows for a more responsive and efficient handling of data processing tasks.

Dataplane's goal is to make it faster and easier to create a data mesh. It has robust data pipelines and automated workflows that can be used by businesses and teams of any size. Dataplane is more user-friendly and places a greater emphasis on performance, security, resilience, and scaling.

Our platform for data discovery and scanning operates without the need for agents, making it simple to integrate with any cloud accounts, including AWS, Azure, and GCP. You won't have to handle any deployments or management tasks. We are compatible with all native cloud data repositories, whether structured or unstructured, across these three major cloud providers. Normalyze efficiently scans both types of data within your cloud environments, collecting only metadata to enhance the Normalyze graph, ensuring that no sensitive information is gathered during the process. The platform visualizes access and trust relationships in real-time, offering detailed context that encompasses fine-grained process names, data store fingerprints, and IAM roles and policies. It enables you to swiftly identify all data stores that may contain sensitive information, uncover every access path, and evaluate potential breach paths according to factors like sensitivity, volume, and permissions, highlighting vulnerabilities that could lead to data breaches. Furthermore, the platform allows for the categorization and identification of sensitive data according to industry standards, including PCI, HIPAA, and GDPR, providing comprehensive compliance support. This holistic approach not only enhances data security but also empowers organizations to maintain regulatory compliance efficiently.

Traditional Data Lakes frequently simplify their role to merely serving as inexpensive raw data repositories, overlooking crucial elements such as data transformation, quality assurance, and security protocols. Consequently, data scientists often find themselves dedicating as much as 80% of their time to the processes of data acquisition, comprehension, and cleansing, which delays their ability to leverage their primary skills effectively. Furthermore, the establishment of traditional Data Lakes tends to occur in isolation by various departments, each utilizing different standards and tools, complicating the implementation of cohesive analytical initiatives. In contrast, Smart Data Lakes address these challenges by offering both architectural and methodological frameworks, alongside a robust toolset designed to create a high-quality data infrastructure. Essential to any contemporary analytics platform, Smart Data Lakes facilitate seamless integration with popular Data Science tools and open-source technologies, including those used for artificial intelligence and machine learning applications. Their cost-effective and scalable storage solutions accommodate a wide range of data types, including unstructured data and intricate data models, thereby enhancing overall analytical capabilities. This adaptability not only streamlines operations but also fosters collaboration across different departments, ultimately leading to more informed decision-making.