Alternatives to Kyligence

Google Cloud is an online service that lets you create everything from simple websites to complex apps for businesses of any size. Customers who are new to the system will receive $300 in credits for testing, deploying, and running workloads. Customers can use up to 25+ products free of charge. Use Google's core data analytics and machine learning. All enterprises can use it. It is secure and fully featured. Use big data to build better products and find answers faster. You can grow from prototypes to production and even to planet-scale without worrying about reliability, capacity or performance. Virtual machines with proven performance/price advantages, to a fully-managed app development platform. High performance, scalable, resilient object storage and databases. Google's private fibre network offers the latest software-defined networking solutions. Fully managed data warehousing and data exploration, Hadoop/Spark and messaging.

Satori is a Data Security Platform (DSP) that enables self-service data and analytics for data-driven companies. With Satori, users have a personal data portal where they can see all available datasets and gain immediate access to them. That means your data consumers get data access in seconds instead of weeks. Satori’s DSP dynamically applies the appropriate security and access policies, reducing manual data engineering work. Satori’s DSP manages access, permissions, security, and compliance policies - all from a single console. Satori continuously classifies sensitive data in all your data stores (databases, data lakes, and data warehouses), and dynamically tracks data usage while applying relevant security policies. Satori enables your data use to scale across the company while meeting all data security and compliance requirements.

Looker reinvents the way business intelligence (BI) works by delivering an entirely new kind of data discovery solution that modernizes BI in three important ways. A simplified web-based stack leverages our 100% in-database architecture, so customers can operate on big data and find the last mile of value in the new era of fast analytic databases. An agile development environment enables today’s data rockstars to model the data and create end-user experiences that make sense for each specific business, transforming data on the way out, rather than on the way in. At the same time, a self-service data-discovery experience works the way the web works, empowering business users to drill into and explore very large datasets without ever leaving the browser. As a result, Looker customers enjoy the power of traditional BI at the speed of the web.

Data integration for hybrid clouds Modern, reliable data integration across both your private cloud and public cloud. All this in real-time, with change data capture and streams. Striim was developed by the executive and technical team at GoldenGate Software. They have decades of experience in mission critical enterprise workloads. Striim can be deployed in your environment as a distributed platform or in the cloud. Your team can easily adjust the scaleability of Striim. Striim is fully secured with HIPAA compliance and GDPR compliance. Built from the ground up to support modern enterprise workloads, whether they are hosted in the cloud or on-premise. Drag and drop to create data flows among your sources and targets. Real-time SQL queries allow you to process, enrich, and analyze streaming data.

Business Process Management Software (BPMS & BPM Workflow Automation Software). Companies require support for workflow, forms, compliance, as well as automation routing. Low-code options make it easy to create and edit workflows. Our best-in class forms capabilities make it easy to quickly build forms, logic, and workflows for forms driven workflow processes. Many systems are already in place and need to be integrated. Our business process integrations between systems are loosely-coupled and intelligently integrated. FlowWright allows you to access standard metrics as well as those you create when automating your business. BPM analytics are an integral part of any BPM workflow management solution. FlowWright is available as a cloud solution, or in an on-premise or.NET hosted environment, including AWS and Azure. It was developed in.NET Foundation C# code. All tools are browser-based and do not require plug-ins.

Amazon CloudWatch serves as a comprehensive monitoring and observability tool designed specifically for DevOps professionals, software developers, site reliability engineers, and IT administrators. This service equips users with essential data and actionable insights necessary for overseeing applications, reacting to performance shifts across systems, enhancing resource efficiency, and gaining an integrated perspective on operational health. By gathering monitoring and operational information in the forms of logs, metrics, and events, CloudWatch delivers a cohesive view of AWS resources, applications, and services, including those deployed on-premises. Users can leverage CloudWatch to identify unusual patterns within their environments, establish alerts, visualize logs alongside metrics, automate responses, troubleshoot problems, and unearth insights that contribute to application stability. Additionally, CloudWatch alarms continuously monitor your specified metric values against established thresholds or those generated through machine learning models to effectively spot any anomalous activities. This functionality ensures that users can maintain optimal performance and reliability across their systems.

Amazon Redshift is a modern cloud data warehouse platform developed by AWS to help organizations run large-scale analytics and AI-powered workloads with exceptional speed, scalability, and cost efficiency. The solution enables businesses to unify data across Amazon S3 data lakes, Redshift data warehouses, and federated third-party data sources using a secure and open lakehouse architecture. Redshift supports SQL-based analytics and provides organizations with the ability to process massive volumes of data while maintaining strong price-performance advantages compared to traditional cloud data warehouse platforms. The platform features AWS Graviton-powered RG instances that deliver faster query performance and lower operational costs while supporting open data formats such as Apache Iceberg and Apache Parquet. Redshift Serverless allows users to run analytics without provisioning or managing infrastructure, making it easier for teams to scale resources dynamically based on workload demands. The solution also includes zero-ETL integrations that enable near real-time analytics by connecting operational databases, streaming systems, and enterprise applications without requiring complex data engineering workflows. Amazon Redshift integrates with Amazon SageMaker for unified analytics and machine learning capabilities while also supporting Amazon Bedrock for generative AI applications and structured knowledge management. Organizations across industries use Redshift to improve forecasting, optimize business intelligence, accelerate machine learning operations, and monetize data assets more effectively.

Kyvos is a semantic layer for AI and BI. It gives organizations a single, consistent, business-friendly view of their entire data estate. By standardizing how data is defined and understood, Kyvos eliminates metric drift across BI tools and ensures that LLMs and AI agents work with governed business semantics rather than raw tables. Kyvos also delivers lightning-fast analytics at massive scale and high concurrency — including granular multidimensional analysis on the cloud — without the sluggish query times and escalating cloud costs that typically come with it. What Kyvos Solves? Organizations today operate across multiple data platforms, analytics tools, and AI interfaces. Without a unified semantic foundation, the same business question can return different answers depending on the tool, query logic, or dataset used. And as data volumes grow into billions of rows, querying the full breadth and depth of an organization's data becomes slow and expensive — forcing teams to work with limited slices rather than the complete picture. Kyvos addresses both by creating a universal semantic layer across the data estate — standardizing how business data is defined and understood — while delivering high-performance analytics that remain fast and cost-efficient regardless of data scale and user concurrency. The result is “one view, one meaning, one truth” of enterprise data, while delivering fast, scalable analytics across LLMs, AI agents and BI tools.

Microsoft Azure serves as a versatile cloud computing platform that facilitates swift and secure development, testing, and management of applications. With Azure, you can innovate purposefully, transforming your concepts into actionable solutions through access to over 100 services that enable you to build, deploy, and manage applications in various environments—be it in the cloud, on-premises, or at the edge—utilizing your preferred tools and frameworks. The continuous advancements from Microsoft empower your current development needs while also aligning with your future product aspirations. Committed to open-source principles and accommodating all programming languages and frameworks, Azure allows you the freedom to build in your desired manner and deploy wherever it suits you best. Whether you're operating on-premises, in the cloud, or at the edge, Azure is ready to adapt to your current setup. Additionally, it offers services tailored for hybrid cloud environments, enabling seamless integration and management. Security is a foundational aspect, reinforced by a team of experts and proactive compliance measures that are trusted by enterprises, governments, and startups alike. Ultimately, Azure represents a reliable cloud solution, backed by impressive performance metrics that validate its trustworthiness. This platform not only meets your needs today but also equips you for the evolving challenges of tomorrow.

Utilize widely-used open-source frameworks like Apache Hadoop, Spark, Hive, and Kafka with Azure HDInsight, a customizable and enterprise-level service designed for open-source analytics. Effortlessly manage vast data sets while leveraging the extensive open-source project ecosystem alongside Azure’s global capabilities. Transitioning your big data workloads to the cloud is straightforward and efficient. You can swiftly deploy open-source projects and clusters without the hassle of hardware installation or infrastructure management. The big data clusters are designed to minimize expenses through features like autoscaling and pricing tiers that let you pay solely for your actual usage. With industry-leading security and compliance validated by over 30 certifications, your data is well protected. Additionally, Azure HDInsight ensures you remain current with the optimized components tailored for technologies such as Hadoop and Spark, providing an efficient and reliable solution for your analytics needs. This service not only streamlines processes but also enhances collaboration across teams.

AtScale streamlines and speeds up business intelligence processes, leading to quicker insights, improved decision-making, and enhanced returns on your cloud analytics investments. It removes the need for tedious data engineering tasks, such as gathering, maintaining, and preparing data for analysis. By centralizing business definitions, AtScale ensures that KPI reporting remains consistent across various BI tools. The platform not only accelerates the time it takes to gain insights from data but also optimizes the management of cloud computing expenses. Additionally, it allows organizations to utilize their existing data security protocols for analytics, regardless of where the data is stored. AtScale’s Insights workbooks and models enable users to conduct Cloud OLAP multidimensional analysis on datasets sourced from numerous providers without the requirement for data preparation or engineering. With user-friendly built-in dimensions and measures, businesses can swiftly extract valuable insights that inform their strategic decisions, enhancing their overall operational efficiency. This capability empowers teams to focus on analysis rather than data handling, leading to sustained growth and innovation.

UnlimitedAnalytics® serves as a comprehensive enterprise solution designed for data analytics, business intelligence, capacity management, data warehousing, and reporting, employing a versatile algorithm that accommodates various data sources to form a streamlined, cohesive multi-dimensional data warehouse. After data is uploaded for processing and analysis, users are empowered to generate both detailed and executive-level graphic or tabular reports effortlessly. This capability is facilitated by the solution's ability to construct dynamic and real-time multi-dimensional data cubes, such as OLAP, PIVOT, and CROSSTAB, all without the need for any coding or scripting. For organizations aiming to transform vast amounts of data from diverse origins into actionable business insights, this tool becomes an invaluable asset for enhancing operational, tactical, and strategic decision-making processes. Additionally, it allows teams to visualize data trends and patterns, further enhancing their analytical capabilities.

Multi-cloud data security with a single pane of glass Industry's first SaaS access governance solution. Cloud is fragmented and data is scattered across different systems. Sensitive data is difficult to access and control due to limited visibility. Complex data onboarding hinders data scientist productivity. Data governance across services can be manual and fragmented. It can be time-consuming to securely move data to the cloud. Maximize visibility and assess the risk of sensitive data distributed across multiple cloud service providers. One system that enables you to manage multiple cloud services' data policies in a single place. Support RTBF, GDPR and other compliance requests across multiple cloud service providers. Securely move data to the cloud and enable Apache Ranger compliance policies. It is easier and quicker to transform sensitive data across multiple cloud databases and analytical platforms using one integrated system.

Gain access to detailed data for seamless analysis of billions of rows and achieve real-time reporting in mere seconds! Sigview, a plug-and-play data analytics tool from Sigmoid, simplifies exploratory data analysis and is built on Apache Spark, allowing users to delve into extensive data sets almost instantly. With approximately 30,000 users worldwide leveraging this tool to evaluate billions of ad impressions, Sigview is expertly designed to provide immediate access to both programmatic and non-programmatic data while generating real-time reports. Whether your aim is to enhance ad campaign performance, uncover new inventory, or explore revenue opportunities in an evolving market, Sigview serves as the ultimate platform for your reporting requirements. It seamlessly connects to various data sources, including DFP, Pixel Servers, and audience viewability partners, enabling the ingestion of data in any format and location while ensuring data latency remains below 15 minutes. This capability allows users to make informed decisions quickly and adapt to changing business landscapes with confidence.

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.

AnalyticDB for MySQL is an efficient data warehousing solution that boasts security, stability, and user-friendliness. This platform facilitates the creation of online statistical reports and multidimensional analysis applications while supporting real-time data warehousing. Utilizing a distributed computing framework, AnalyticDB for MySQL leverages the cloud’s elastic scaling to process vast amounts of data, handling tens of billions of records instantaneously. It organizes data according to relational models and employs SQL for flexible computation and analysis. Additionally, the service simplifies database management, allowing users to scale nodes and adjust instance sizes with ease. With its suite of visualization and ETL tools, it enhances enterprise data processing significantly. Moreover, this system enables rapid multidimensional analysis, offering the capability to sift through extensive datasets in mere milliseconds. It is a powerful resource for organizations looking to optimize their data strategies and gain insights quickly.

Vertica is a high-performance enterprise analytics and data warehousing platform that enables organizations to process large-scale data workloads, advanced analytics, and AI applications across cloud, on-premises, and hybrid infrastructures. Acquired by Rocket Software, Vertica expands Rocket’s modernization portfolio by adding enterprise-grade analytics and artificial intelligence capabilities to mission-critical systems modernization. The platform is designed to help enterprises unlock the value of their data through fast query performance, scalable analytics, and AI-driven insights that support modern business operations and digital transformation initiatives. Vertica supports flexible deployment models including private cloud, public cloud, managed services, and on-premises environments, allowing organizations to modernize data infrastructure without being restricted to a single deployment strategy. The platform enables businesses to run advanced analytics and generative AI directly against trusted enterprise data while maintaining stability, governance, and operational performance. Vertica also complements Rocket Software’s DataEdge and ContentEdge solutions by creating a unified ecosystem for enterprise data integration, modernization, governance, and analytics. Organizations use Vertica to accelerate reporting, improve operational intelligence, optimize enterprise workloads, and drive faster data-driven decision-making across large-scale business environments. The platform is designed for enterprises that require scalable analytics, hybrid cloud flexibility, and AI-ready infrastructure for mission-critical systems modernization.

Elastic is a search company. Elasticsearch, Kibana Beats, Logstash, and Elasticsearch are the founders of the ElasticStack. These SaaS offerings allow data to be used in real-time and at scale for analytics, security, search, logging, security, and search. Elastic has over 100,000 members in 45 countries. Elastic's products have been downloaded more than 400 million times since their initial release. Today, thousands of organizations including Cisco, eBay and Dell, Goldman Sachs and Groupon, HP and Microsoft, as well as Netflix, Uber, Verizon and Yelp use Elastic Stack and Elastic Cloud to power mission critical systems that generate new revenue opportunities and huge cost savings. Elastic is headquartered in Amsterdam, The Netherlands and Mountain View, California. It has more than 1,000 employees in over 35 countries.

EMR serves as a comprehensive enterprise-grade big data platform, offering cluster, job, and data management functionalities that leverage various open-source technologies, including Hadoop, Spark, Kafka, Flink, and Storm. Alibaba Cloud Elastic MapReduce (EMR) is specifically designed for big data processing within the Alibaba Cloud ecosystem. Built on Alibaba Cloud's ECS instances, EMR integrates the capabilities of open-source Apache Hadoop and Apache Spark. This platform enables users to utilize components from the Hadoop and Spark ecosystems, such as Apache Hive, Apache Kafka, Flink, Druid, and TensorFlow, for effective data analysis and processing. Users can seamlessly process data stored across multiple Alibaba Cloud storage solutions, including Object Storage Service (OSS), Log Service (SLS), and Relational Database Service (RDS). EMR also simplifies cluster creation, allowing users to establish clusters rapidly without the hassle of hardware and software configuration. Additionally, all maintenance tasks can be managed efficiently through its user-friendly web interface, making it accessible for various users regardless of their technical expertise.

Amazon EMR stands as the leading cloud-based big data solution for handling extensive datasets through popular open-source frameworks like Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto. This platform enables you to conduct Petabyte-scale analyses at a cost that is less than half of traditional on-premises systems and delivers performance more than three times faster than typical Apache Spark operations. For short-duration tasks, you have the flexibility to quickly launch and terminate clusters, incurring charges only for the seconds the instances are active. In contrast, for extended workloads, you can establish highly available clusters that automatically adapt to fluctuating demand. Additionally, if you already utilize open-source technologies like Apache Spark and Apache Hive on-premises, you can seamlessly operate EMR clusters on AWS Outposts. Furthermore, you can leverage open-source machine learning libraries such as Apache Spark MLlib, TensorFlow, and Apache MXNet for data analysis. Integrating with Amazon SageMaker Studio allows for efficient large-scale model training, comprehensive analysis, and detailed reporting, enhancing your data processing capabilities even further. This robust infrastructure is ideal for organizations seeking to maximize efficiency while minimizing costs in their data operations.

CelerData is an advanced SQL engine designed to enable high-performance analytics directly on data lakehouses, removing the necessity for conventional data warehouse ingestion processes. It achieves impressive query speeds in mere seconds, facilitates on-the-fly JOIN operations without incurring expensive denormalization, and streamlines system architecture by enabling users to execute intensive workloads on open format tables. Based on the open-source StarRocks engine, this platform surpasses older query engines like Trino, ClickHouse, and Apache Druid in terms of latency, concurrency, and cost efficiency. With its cloud-managed service operating within your own VPC, users maintain control over their infrastructure and data ownership while CelerData manages the upkeep and optimization tasks. This platform is poised to support real-time OLAP, business intelligence, and customer-facing analytics applications, and it has garnered the trust of major enterprise clients, such as Pinterest, Coinbase, and Fanatics, who have realized significant improvements in latency and cost savings. Beyond enhancing performance, CelerData’s capabilities allow businesses to harness their data more effectively, ensuring they remain competitive in a data-driven landscape.

HiBob’s Finance Suite is an integrated financial planning and analysis solution designed for fast-growing global businesses. It connects financial data with workforce insights to provide a single source of truth. Teams gain instant visibility into spending, runway, and performance through real-time reporting. The platform supports collaborative budgeting across departments with live people data synchronization. Finance leaders can build flexible forecasts using connected financial models and what-if scenarios. AI-powered workflows help summarize trends and create board-ready insights quickly. Custom metrics and out-of-the-box KPIs make analysis more efficient. Seamless integrations ensure data flows smoothly from existing tools. HR and Finance teams work together more strategically using shared planning tools. HiBob’s Finance Suite helps organizations control costs while supporting sustainable growth.

HEAVY.AI is a pioneer in accelerated analysis. The HEAVY.AI platform can be used by government and business to uncover insights in data that is beyond the reach of traditional analytics tools. The platform harnesses the huge parallelism of modern CPU/GPU hardware and is available both in the cloud or on-premise. HEAVY.AI was developed from research at Harvard and MIT Computer Science and Artificial Intelligence Laboratory. You can go beyond traditional BI and GIS and extract high-quality information from large datasets with no lag by leveraging modern GPU and CPU hardware. To get a complete picture of what, when and where, unify and explore large geospatial or time-series data sets. Combining interactive visual analytics, hardware accelerated SQL, advanced analytics & data sciences frameworks, you can find the opportunity and risk in your enterprise when it matters most.

Oracle Big Data Preparation Cloud Service is a comprehensive managed Platform as a Service (PaaS) solution that facilitates the swift ingestion, correction, enhancement, and publication of extensive data sets while providing complete visibility in a user-friendly environment. This service allows for seamless integration with other Oracle Cloud Services, like the Oracle Business Intelligence Cloud Service, enabling deeper downstream analysis. Key functionalities include profile metrics and visualizations, which become available once a data set is ingested, offering a visual representation of profile results and summaries for each profiled column, along with outcomes from duplicate entity assessments performed on the entire data set. Users can conveniently visualize governance tasks on the service's Home page, which features accessible runtime metrics, data health reports, and alerts that keep them informed. Additionally, you can monitor your transformation processes and verify that files are accurately processed, while also gaining insights into the complete data pipeline, from initial ingestion through to enrichment and final publication. The platform ensures that users have the tools needed to maintain control over their data management tasks effectively.

Dremio provides lightning-fast queries as well as a self-service semantic layer directly to your data lake storage. No data moving to proprietary data warehouses, and no cubes, aggregation tables, or extracts. Data architects have flexibility and control, while data consumers have self-service. Apache Arrow and Dremio technologies such as Data Reflections, Columnar Cloud Cache(C3), and Predictive Pipelining combine to make it easy to query your data lake storage. An abstraction layer allows IT to apply security and business meaning while allowing analysts and data scientists access data to explore it and create new virtual datasets. Dremio's semantic layers is an integrated searchable catalog that indexes all your metadata so business users can make sense of your data. The semantic layer is made up of virtual datasets and spaces, which are all searchable and indexed.

Transform your big data processes and create intelligent knowledge repositories with the Data Lake Governance Center (DGC), a comprehensive platform for managing all facets of data lake operations, including design, development, integration, quality, and asset management. With its intuitive visual interface, you can establish a robust data lake governance framework that enhances the efficiency of your data lifecycle management. Leverage analytics and metrics to uphold strong governance throughout your organization, while also defining and tracking data standards with the ability to receive real-time alerts. Accelerate the development of data lakes by easily configuring data integrations, models, and cleansing protocols to facilitate the identification of trustworthy data sources. Enhance the overall business value derived from your data assets. DGC enables the creation of tailored solutions for various applications, such as smart government, smart taxation, and smart campuses, while providing valuable insights into sensitive information across your organization. Additionally, DGC empowers businesses to establish comprehensive catalogs, classifications, and terminologies for their data. This holistic approach ensures that data governance is not just a task, but a core aspect of your enterprise's strategy.

When you have the expertise of an enterprise partner combined with a scalable, easy-to-use data management suite, you can take back control of your data, access it from anywhere, ensure security and compliance, and unlock its power to grow your business. Why Use Sesame Software? Relational Junction builds, populates, and incrementally refreshes your data automatically. Enhance Data Quality - Convert data from multiple sources into a consistent format – leading to more accurate data, which provides the basis for solid decisions. Gain Insights - Automate the update of information into a central location, you can use your in-house BI tools to build useful reports to avoid costly mistakes. Fixed Price - Avoid high consumption costs with yearly fixed prices and multi-year discounts no matter your data volume.

Eliminate the tedious search for metrics and gain immediate access to the narrative your business data unfolds through a unified analytics platform, enabling you to make quicker, data-driven choices. In the current landscape, leveraging data is crucial for sound decision-making. Cognytics integrates seamlessly with your existing ERP systems, consolidating vital datasets to produce robust dashboards. Obtain your insights from a singular, reliable source. Digging for data can quickly devolve into a time-consuming and costly endeavor. Our business intelligence (BI) dashboards are intricately woven into your primary ECI software, allowing you to access important metrics without switching between different platforms. Streamline the analysis process while enhancing the effectiveness of your decisions. Given the prevalence of big data today, visualization tools have become indispensable for dissecting extensive information sets and facilitating informed choices. Cognytics dashboards equip your team with immediate access to insights within the applications they frequently use, ultimately fostering a more efficient workflow. By harnessing these tools, you can empower your organization to thrive in a data-driven environment.

Keen is a fully managed event streaming platform. Our real-time data pipeline, built on Apache Kafka, makes it easy to collect large amounts of event data. Keen's powerful REST APIs and SDKs allow you to collect event data from any device connected to the internet. Our platform makes it possible to securely store your data, reducing operational and delivery risks with Keen. Apache Cassandra's storage infrastructure ensures data is completely secure by transferring it via HTTPS and TLS. The data is then stored with multilayer AES encryption. Access Keys allow you to present data in an arbitrary way without having to re-architect or re-architect the data model. Role-based Access Control allows for completely customizable permission levels, down to specific queries or data points.

CloudMonitor is a service that gathers monitoring metrics for Alibaba Cloud resources as well as custom metrics tailored to your needs. This tool is designed to help you assess the availability of your services and enables you to configure alarms for specific performance indicators. With CloudMonitor, you can gain insights into the utilization of cloud resources, along with the overall health and status of your business, which empowers you to respond quickly when an alarm goes off to maintain application availability. The setup process requires no coding, allowing you to establish CloudMonitor and configure alarms easily through a user-friendly wizard in just a few steps. You have the flexibility to create alarms for various scenarios and can choose from multiple notification methods. This all-encompassing service not only tracks fundamental resources and application performance but also caters to unique business metrics, facilitating the management of cloud resources across different applications organized by groups for better oversight. Overall, CloudMonitor helps ensure that you stay informed and proactive in managing the health of your cloud infrastructure.

At the core of our innovative approach lies in-data computing, a cutting-edge technology aimed at efficiently processing substantial volumes of data. Our leading product, BigObject, is a prime example of this technology; it is a time series database purposefully created to enable rapid storage and management of vast data sets. Leveraging in-data computing, BigObject has the capability to swiftly and continuously address diverse data streams without interruption. This time series database excels in both high-speed storage and data analysis, showcasing remarkable performance alongside robust complex query functionalities. By transitioning from a traditional relational data structure to a time-series model, it harnesses in-data computing to enhance overall database efficiency. The foundation of our technology is an abstract model, wherein all data resides within an infinite and persistent memory space, facilitating seamless storage and computation. This unique architecture not only optimizes performance but also paves the way for future advancements in data processing capabilities.

An AI-driven self-service platform for advanced analytics allows users to connect diverse data sources and create visualizations effortlessly, eliminating the need for programming skills. This cloud-native solution delivers high-quality data and intelligent real-time insights across the organization with a no-code approach. Users can link various data sources, regardless of their formats, enabling the detection of underlying issues. The platform significantly reduces the time taken from sourcing to targeting data, while providing analytics accessible to those without technical expertise. With real-time data updates, users can connect any kind of data source, streaming it to a data lake at defined intervals, and visualize the information through sophisticated interactive dashboards. It combines descriptive, predictive, and prescriptive analytics in one platform, utilizing the capabilities of a search engine alongside advanced visualization techniques. There’s no need for conventional technology to explore data in multiple visualization styles. Users can easily manipulate data through roll-ups, slicing, and dicing, employing various mathematical computations directly within the Bizintel360 visualization environment, thus enhancing their analytical capabilities. This empowers businesses to make data-driven decisions with ease and speed.

Apache DevLake (currently in incubation) consolidates, evaluates, and visualizes disparate data from various DevOps tools to extract valuable insights that promote engineering excellence. In the realm of software development, your data is often scattered across multiple silos and platforms. DevLake bridges these gaps, offering a holistic perspective on your Software Development Life Cycle (SDLC). The platform seamlessly implements metrics, from DORA to scrum retrospectives, with its preconfigured dashboards that align with widely-used frameworks and objectives. It is designed to accommodate teams of diverse sizes and structures, while also providing the flexibility to incorporate additional data sources, metrics, and dashboards through its adaptable data collection and transformation framework. You can easily select, modify, and schedule data synchronization from your preferred sources using the configuration interface. Gain insights by exploring pre-built dashboards tailored for various use cases and leverage the metrics to enhance your engineering processes. Additionally, you have the freedom to customize your own metrics and dashboards using SQL, thereby expanding the potential applications of DevLake. This versatility ensures that DevLake can evolve alongside your team's needs and the ever-changing demands of software development.

Imply is a cutting-edge analytics platform that leverages Apache Druid to manage extensive, high-performance OLAP (Online Analytical Processing) tasks in real-time. It excels at ingesting data instantly, delivering rapid query results, and enabling intricate analytical inquiries across vast datasets while maintaining low latency. This platform is specifically designed for enterprises that require engaging analytics, real-time dashboards, and data-centric decision-making on a large scale. Users benefit from an intuitive interface for exploring data, enhanced by features like multi-tenancy, detailed access controls, and operational insights. Its distributed architecture and ability to scale make Imply particularly advantageous for applications in streaming data analysis, business intelligence, and real-time monitoring across various sectors. Furthermore, its capabilities ensure that organizations can efficiently adapt to increasing data demands and quickly derive actionable insights from their data.

Maximize your resources. Optimize your cloud, platforms, and software. This is the new definition of application and API network operations management. All your API, application, and network operations are managed in the same place, with the same governance rules, observability and auditing. Zero-trust micro-segmentation and omni-directional traffic splitting, infrastructure agnostic authentication, and traffic management are all available to protect your resources. IT-informed decision making is possible. Massive IT operations data is generated by API, application and network monitoring and control. It is possible to access it in real-time using AI. Grey Matter makes integration easy and standardizes aggregation of all IT Operations data. You can fully leverage your mesh telemetry to secure and flexiblely future-proof your hybrid infrastructure.

Specifically designed to address the distinct monitoring needs of cloud-native environments, this solution has been developed from the ground up to manage the substantial volume of monitoring data generated by cloud-native applications. It serves as a unified platform for business stakeholders, application developers, and infrastructure engineers to troubleshoot problems across the entire technology stack. Each use case is catered to, ranging from sub-second data for ongoing deployments to hourly data for capacity planning. The one-click deployment feature accommodates Prometheus and StatsD ingestion protocols seamlessly. It offers storage and indexing capabilities for both Prometheus and Graphite data types within a single framework. Furthermore, it includes integrated Grafana-compatible dashboards that fully support PromQL and Graphite queries, along with a reliable alerting engine that can connect with services like PagerDuty, Slack, OpsGenie, and webhooks. The system is capable of ingesting and querying billions of metric data points every second, enabling rapid alert triggering, dashboard access, and issue detection within just one second. Additionally, it ensures data reliability by maintaining three consistent copies across various failure domains, thereby reinforcing its robustness in cloud-native monitoring.

Achieve a comprehensive understanding of your applications' and infrastructure's performance, availability, and overall health. Capture real-time metrics across multicloud and hybrid environments seamlessly. Implement Site Reliability Engineering (SRE) best practices, which are widely adopted by Google, focusing on Service Level Objectives (SLOs) and Service Level Indicators (SLIs). Utilize dashboards and charts to visualize insights and set up alerts for timely notifications. Enhance teamwork by integrating with tools like Slack, PagerDuty, and other incident management platforms. Leverage day zero integration specifically designed for Google Cloud metrics. Cloud Monitoring simplifies the process with automatic, preconfigured dashboards for Google Cloud services while also accommodating hybrid and multicloud monitoring needs. A rich query language presents metrics, events, and metadata, aiding in the identification of issues and the discovery of trends. Service-level objectives enhance user experience and foster better collaboration with development teams. With one unified service for metrics, uptime monitoring, dashboards, and alerts, you can minimize the time wasted switching between different systems and streamline operations even further. This holistic approach not only enhances operational efficiency but also contributes to a more proactive management of your IT resources.

Upsolver makes it easy to create a governed data lake, manage, integrate, and prepare streaming data for analysis. Only use auto-generated schema on-read SQL to create pipelines. A visual IDE that makes it easy to build pipelines. Add Upserts to data lake tables. Mix streaming and large-scale batch data. Automated schema evolution and reprocessing of previous state. Automated orchestration of pipelines (no Dags). Fully-managed execution at scale Strong consistency guarantee over object storage Nearly zero maintenance overhead for analytics-ready information. Integral hygiene for data lake tables, including columnar formats, partitioning and compaction, as well as vacuuming. Low cost, 100,000 events per second (billions every day) Continuous lock-free compaction to eliminate the "small file" problem. Parquet-based tables are ideal for quick queries.

The PI System unveils operational insights and opens up new avenues for innovation. By facilitating digital transformation, the PI System harnesses reliable, high-quality operational data to drive progress. It allows for data collection, enhancement, and real-time delivery from any location. This empowers both engineers and operators alike, while also speeding up the efforts of analysts and data scientists. Furthermore, it creates opportunities for new business ventures. The system is capable of gathering real-time data from a multitude of assets, including legacy systems, proprietary technologies, remote devices, mobile units, and IIoT devices. With the PI System, your data becomes accessible regardless of its location or format. It enables the storage of decades of data with sub-second precision, offering you immediate access to high-fidelity historical, real-time, and predictive data crucial for maintaining essential operations and gaining valuable business insights. By incorporating intuitive labels and metadata, the system enhances the meaning of data. You can also establish data hierarchies that mirror your operational and reporting structures. With the addition of context, data points transform from mere numbers into a comprehensive narrative that encompasses the entire picture, allowing informed decision-making. This holistic view ultimately leads to more strategic planning and operational excellence.

CM is enabled by default for every Tencent Cloud account. Once you have purchased Tencent Cloud services, you can access the CM console directly to monitor the operational status of your products and configure alerts as needed. The system can gather data for all metrics in mere seconds, allowing it to detect even the slightest variations, thus enhancing your cloud product monitoring experience. CM offers complimentary storage for monitoring data collected every few seconds, available for up to 24 hours, and you can easily view and download this information online. Additionally, CM allows for the configuration of personalized trigger rules for monitoring metrics, facilitating accurate alerts across various dimensions such as thresholds, timeframes, duration, and frequency of alarms. On top of that, it ensures that alarms are communicated promptly through multiple channels including email, SMS, WeChat, and phone calls, providing users with comprehensive coverage of their monitoring needs. This robust system ultimately enhances your ability to maintain optimal product performance and respond quickly to any issues that may arise.

iceDQ, a DataOps platform that allows monitoring and testing, is a DataOps platform. iceDQ is an agile rules engine that automates ETL Testing, Data Migration Testing and Big Data Testing. It increases productivity and reduces project timelines for testing data warehouses and ETL projects. Identify data problems in your Data Warehouse, Big Data, and Data Migration Projects. The iceDQ platform can transform your ETL or Data Warehouse Testing landscape. It automates it from end to end, allowing the user to focus on analyzing the issues and fixing them. The first edition of iceDQ was designed to validate and test any volume of data with our in-memory engine. It can perform complex validation using SQL and Groovy. It is optimized for Data Warehouse Testing. It scales based upon the number of cores on a server and is 5X faster that the standard edition.

IBM Db2 Big SQL is a sophisticated hybrid SQL-on-Hadoop engine that facilitates secure and advanced data querying across a range of enterprise big data sources, such as Hadoop, object storage, and data warehouses. This enterprise-grade engine adheres to ANSI standards and provides massively parallel processing (MPP) capabilities, enhancing the efficiency of data queries. With Db2 Big SQL, users can execute a single database connection or query that spans diverse sources, including Hadoop HDFS, WebHDFS, relational databases, NoSQL databases, and object storage solutions. It offers numerous advantages, including low latency, high performance, robust data security, compatibility with SQL standards, and powerful federation features, enabling both ad hoc and complex queries. Currently, Db2 Big SQL is offered in two distinct variations: one that integrates seamlessly with Cloudera Data Platform and another as a cloud-native service on the IBM Cloud Pak® for Data platform. This versatility allows organizations to access and analyze data effectively, performing queries on both batch and real-time data across various sources, thus streamlining their data operations and decision-making processes. In essence, Db2 Big SQL provides a comprehensive solution for managing and querying extensive datasets in an increasingly complex data landscape.

Utilize Azure Resource Manager to quickly establish and deploy an Azure Analysis Services instance, allowing for the swift transfer of your existing models to take full advantage of the cloud's scalability, flexibility, and management features. You can easily scale up, scale down, or temporarily suspend the service, ensuring you only pay for what you actually utilize. Integrate data from diverse sources into a cohesive and reliable BI semantic model that is user-friendly and straightforward. By simplifying the representation of data and its foundational structure, you empower business users with self-service capabilities and facilitate data exploration. This approach significantly accelerates the time-to-insight for large and intricate datasets, ensuring that your BI solutions are responsive and aligned with the demands of your organization. Additionally, leverage DirectQuery to connect with real-time operational data, enabling you to monitor your business dynamics closely. Finally, enhance your data visualization experience by employing your preferred data visualization tools, making insights more accessible and actionable. This comprehensive solution not only enhances data usability but also drives better decision-making within the organization.

Unlike most data management systems, PHEMI Health DataLab is built with Privacy-by-Design principles, not as an add-on. This means privacy and data governance are built-in from the ground up, providing you with distinct advantages: Lets analysts work with data without breaching privacy guidelines Includes a comprehensive, extensible library of de-identification algorithms to hide, mask, truncate, group, and anonymize data. Creates dataset-specific or system-wide pseudonyms enabling linking and sharing of data without risking data leakage. Collects audit logs concerning not only what changes were made to the PHEMI system, but also data access patterns. Automatically generates human and machine-readable de- identification reports to meet your enterprise governance risk and compliance guidelines. Rather than a policy per data access point, PHEMI gives you the advantage of one central policy for all access patterns, whether Spark, ODBC, REST, export, and more

Cazena's Instant Data Lake significantly reduces the time needed for analytics and AI/ML from several months to just a few minutes. Utilizing its unique automated data platform, Cazena introduces a pioneering SaaS model for data lakes, requiring no operational input from users. Businesses today seek a data lake that can seamlessly accommodate all their data and essential tools for analytics, machine learning, and artificial intelligence. For a data lake to be truly effective, it must ensure secure data ingestion, provide adaptable data storage, manage access and identities, facilitate integration with various tools, and optimize performance among other features. Building cloud data lakes independently can be quite complex and typically necessitates costly specialized teams. Cazena's Instant Cloud Data Lakes are not only designed to be readily operational for data loading and analytics but also come with a fully automated setup. Supported by Cazena’s SaaS Platform, they offer ongoing operational support and self-service access through the user-friendly Cazena SaaS Console. With Cazena's Instant Data Lakes, users have a completely turnkey solution that is primed for secure data ingestion, efficient storage, and comprehensive analytics capabilities, making it an invaluable resource for enterprises looking to harness their data effectively and swiftly.