Alternatives to Oracle Cloud Infrastructure Data Lakehouse

Open, hybrid data lakes for AI and analytics can be used to put your data to use, wherever it is located. Connect your data in any format and from anywhere. Access it through a shared metadata layer. By matching the right workloads to the right query engines, you can optimize workloads in terms of price and performance. Integrate natural-language semantic searching without the need for SQL to unlock AI insights faster. Manage and prepare trusted datasets to improve the accuracy and relevance of your AI applications. Use all of your data everywhere. Watsonx.data offers the speed and flexibility of a warehouse, along with special features that support AI. This allows you to scale AI and analytics throughout your business. Choose the right engines to suit your workloads. You can manage your cost, performance and capability by choosing from a variety of open engines, including Presto C++ and Spark Milvus.

Amazon Redshift is preferred by more customers than any other cloud data storage. Redshift powers analytic workloads for Fortune 500 companies and startups, as well as everything in between. Redshift has helped Lyft grow from a startup to multi-billion-dollar enterprises. It's easier than any other data warehouse to gain new insights from all of your data. Redshift allows you to query petabytes (or more) of structured and semi-structured information across your operational database, data warehouse, and data lake using standard SQL. Redshift allows you to save your queries to your S3 database using open formats such as Apache Parquet. This allows you to further analyze other analytics services like Amazon EMR and Amazon Athena. Redshift is the fastest cloud data warehouse in the world and it gets faster each year. The new RA3 instances can be used for performance-intensive workloads to achieve up to 3x the performance compared to any cloud data warehouse.

BigLake is a storage platform that unifies data warehouses, lakes and allows BigQuery and open-source frameworks such as Spark to access data with fine-grained control. BigLake offers accelerated query performance across multicloud storage and open formats like Apache Iceberg. You can store one copy of your data across all data warehouses and lakes. Multi-cloud governance and fine-grained access control for distributed data. Integration with open-source analytics tools, and open data formats is seamless. You can unlock analytics on distributed data no matter where it is stored. While choosing the best open-source or cloud-native analytics tools over a single copy, you can also access analytics on distributed data. Fine-grained access control for open source engines such as Apache Spark, Presto and Trino and open formats like Parquet. BigQuery supports performant queries on data lakes. Integrates with Dataplex for management at scale, including logical organization.

Archon Data Store™ is an open-source archive lakehouse platform that allows you to store, manage and gain insights from large volumes of data. Its minimal footprint and compliance features enable large-scale processing and analysis of structured and unstructured data within your organization. Archon Data Store combines data warehouses, data lakes and other features into a single platform. This unified approach eliminates silos of data, streamlining workflows in data engineering, analytics and data science. Archon Data Store ensures data integrity through metadata centralization, optimized storage, and distributed computing. Its common approach to managing data, securing it, and governing it helps you innovate faster and operate more efficiently. Archon Data Store is a single platform that archives and analyzes all of your organization's data, while providing operational efficiencies.

Limited competition due to high barriers to entry, specialized knowledge, massive capital requirements, and long times to market. The price and performance of existing platforms are virtually identical, reducing the incentive for a switch. It takes months to migrate from one engine's SQL dialect into another engine's SQL. Interoperable with all major standards. Data leaders in enterprise are being hit by a massive surge in computing demand. They are surprised to discover that 10% of heavy, compute-intensive uses cases consume 80% the cost, engineering efforts and stakeholder complaints. Unfortunately, these workloads are mission-critical and nondiscretionary. e6data increases ROI for enterprises' existing data platforms. e6data’s format-neutral computing is unique in that it is equally efficient and performant for all leading data lakehouse formats.

The Databricks Data Intelligence Platform enables your entire organization to utilize data and AI. It is built on a lakehouse that provides an open, unified platform for all data and governance. It's powered by a Data Intelligence Engine, which understands the uniqueness in your data. Data and AI companies will win in every industry. Databricks can help you achieve your data and AI goals faster and easier. Databricks combines the benefits of a lakehouse with generative AI to power a Data Intelligence Engine which understands the unique semantics in your data. The Databricks Platform can then optimize performance and manage infrastructure according to the unique needs of your business. The Data Intelligence Engine speaks your organization's native language, making it easy to search for and discover new data. It is just like asking a colleague a question.

Secure and manage the data lifecycle, from Edge to AI in any cloud or data centre. Operates on all major public clouds as well as the private cloud with a public experience everywhere. Integrates data management and analytics experiences across the entire data lifecycle. All environments are covered by security, compliance, migration, metadata management. Open source, extensible, and open to multiple data stores. Self-service analytics that is faster, safer, and easier to use. Self-service access to multi-function, integrated analytics on centrally managed business data. This allows for consistent experiences anywhere, whether it is in the cloud or hybrid. You can enjoy consistent data security, governance and lineage as well as deploying the cloud analytics services that business users need. This eliminates the need for shadow IT solutions.

Lyftrondata can help you build a governed lake, data warehouse or migrate from your old database to a modern cloud-based data warehouse. Lyftrondata makes it easy to create and manage all your data workloads from one platform. This includes automatically building your warehouse and pipeline. It's easy to share the data with ANSI SQL, BI/ML and analyze it instantly. You can increase the productivity of your data professionals while reducing your time to value. All data sets can be defined, categorized, and found in one place. These data sets can be shared with experts without coding and used to drive data-driven insights. This data sharing capability is ideal for companies who want to store their data once and share it with others. You can define a dataset, apply SQL transformations, or simply migrate your SQL data processing logic into any cloud data warehouse.

DataLakeHouse.io Data Sync allows users to replicate and synchronize data from operational systems (on-premises and cloud-based SaaS), into destinations of their choice, primarily Cloud Data Warehouses. DLH.io is a tool for marketing teams, but also for any data team in any size organization. It enables business cases to build single source of truth data repositories such as dimensional warehouses, data vaults 2.0, and machine learning workloads. Use cases include technical and functional examples, including: ELT and ETL, Data Warehouses, Pipelines, Analytics, AI & Machine Learning and Data, Marketing and Sales, Retail and FinTech, Restaurants, Manufacturing, Public Sector and more. DataLakeHouse.io has a mission: to orchestrate the data of every organization, especially those who wish to become data-driven or continue their data-driven strategy journey. DataLakeHouse.io, aka DLH.io, allows hundreds of companies manage their cloud data warehousing solutions.

The only fully-managed cloud data lakehouse that can ingest data from all of your sources in minutes, and support all of your query engines on a large scale. All for a fraction the cost. With the ease of fully managed pipelines, you can ingest data from databases and event streams in near-real-time. You can query your data using any engine and support all of your use cases, including BI, AI/ML, real-time analytics and AI/ML. Simple usage-based pricing allows you to cut your costs by up to 50% compared with cloud data warehouses and ETL software. With a fully-managed, highly optimized cloud service, you can deploy in minutes and without any engineering overhead. Unify all your data into a single source and eliminate the need for data to be copied between data lakes and warehouses. Apache Hudi, Apache Iceberg and Delta Lake all offer omnidirectional interoperability, allowing you to choose the best table format for your needs. Configure managed pipelines quickly for database CDC and stream ingestion.

AnalyticsCreator lets you extend and adjust an existing DWH. It is easy to build a solid foundation. The reverse engineering method of AnalyticsCreator allows you to integrate code from an existing DWH app into AC. So, more layers/areas are included in the automation. This will support the change process more extensively. The extension of an manually developed DWH with an ETL/ELT can quickly consume resources and time. Our experience and studies found on the internet have shown that the longer the lifecycle the higher the cost. You can use AnalyticsCreator to design your data model and generate a multitier data warehouse for your Power BI analytical application. The business logic is mapped at one place in AnalyticsCreator.

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.

BryteFlow creates the most efficient and automated environments for analytics. It transforms Amazon S3 into a powerful analytics platform by intelligently leveraging AWS ecosystem to deliver data at lightning speed. It works in conjunction with AWS Lake Formation and automates Modern Data Architecture, ensuring performance and productivity.

Our platform is the only one that offers an end-to–end platform for AI-powered innovation. It can handle everything from data cleansing and structuring to creating and deploying advanced data-science models to infusing advanced analytics algorithms, to infusing Recommendation AI, to deducing outcomes with simple-to-deduce visualization dashboards as well as Explainable AI to track how the outcomes were calculated. Our platform provides a seamless, holistic data science experience. FutureAnalytica offers key features such as a robust Data Lakehouse and an AI Studio. There is also a comprehensive AI Marketplace. You can also get support from a world-class team of data-science experts (on a case-by-case basis). FutureAnalytica will help you save time, effort, and money on your data-science and AI journey. Start discussions with the leadership and then a quick technology assessment within 1-3 days. In 10-18 days, you can create ready-to-integrate AI solutions with FA's fully-automated data science & AI platform.

Discover insights to boost sales growth with code-free, fully automated data pipelines to data lakes and cloud warehouses. Flexible, standards-based platform that unifies sales and marketing data to automate insights and smarter growth. Say goodbye to manual data downloads that are expensive and messy. You will always know exactly what you'll be charged and only pay what you actually use. Access to data-ready data is a great way to fuel your tools. We only work with official APIs as certified developers. Data pipelines from well-known sources are easy to use. These data pipelines are pre-built, pre-transformed and ready to go. Unlock data from Amazon Vendor Central and Amazon Seller Central, Instagram Stories. Teams can quickly and economically realize the value of their data with code-free data ingestion and transformation. Databricks, Amazon Redshift and other trusted data destinations like Databricks or Amazon Redshift ensure that data is always protected.

Mozart Data is the all-in-one modern data platform for consolidating, organizing, and analyzing your data. Set up a modern data stack in an hour, without any engineering. Start getting more out of your data and making data-driven decisions today.

iomete platform combines a powerful lakehouse with an advanced data catalog, SQL editor and BI, providing you with everything you need to become data-driven.

Talend Data Fabric's cloud services are able to efficiently solve all your integration and integrity problems -- on-premises or in cloud, from any source, at any endpoint. Trusted data delivered at the right time for every user. With an intuitive interface and minimal coding, you can easily and quickly integrate data, files, applications, events, and APIs from any source to any location. Integrate quality into data management to ensure compliance with all regulations. This is possible through a collaborative, pervasive, and cohesive approach towards data governance. High quality, reliable data is essential to make informed decisions. It must be derived from real-time and batch processing, and enhanced with market-leading data enrichment and cleaning tools. Make your data more valuable by making it accessible internally and externally. Building APIs is easy with the extensive self-service capabilities. This will improve customer engagement.

Qlik Compose for Data Warehouses offers a modern approach to data warehouse creation and operations by automating and optimising the process. Qlik Compose automates the design of the warehouse, generates ETL code and quickly applies updates, all while leveraging best practices. Qlik Compose for Data Warehouses reduces time, cost, and risk for BI projects whether they are on-premises, or in the cloud. Qlik Compose for Data Lakes automates data pipelines, resulting in analytics-ready data. By automating data ingestion and schema creation, as well as continual updates, organizations can realize a faster return on their existing data lakes investments.

Amazon Security Lake centralizes all security data, including data from AWS, SaaS, on-premises and cloud sources, into a data lake that is stored in your account. Security Lake allows you to gain a better understanding of all your security data throughout your organization. You can also improve your workloads, apps, and data. Security Lake has adopted an open standard, the Open Cybersecurity Schema Framework. The service can combine and normalize security data from AWS as well as a wide range of enterprise data sources with OCSF support. You can use your favorite analytics tools to analyze security data, while maintaining complete control and ownership of that data. Centralize data visibility across all your accounts and AWS regions. Normalizing your security data according to an open standard will streamline your data management.

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.

Your cloud data platform. Access to any data you need with unlimited scalability. All your data is available to you, with the near-infinite performance and concurrency required by your organization. You can seamlessly share and consume shared data across your organization to collaborate and solve your most difficult business problems. You can increase productivity and reduce time to value by collaborating with data professionals to quickly deliver integrated data solutions from any location in your organization. Our technology partners and system integrators can help you deploy Snowflake to your success, no matter if you are moving data into Snowflake.

AnalyticDB for MySQL, a high-performance data warehouse service, is safe, stable, and simple to use. It makes it easy to create online statistical reports, multidimensional analyses solutions, and real time data warehouses. AnalyticDB for MySQL uses distributed computing architecture which allows it to use elastic scaling capabilities of the cloud to compute tens to billions of data records in real-time. AnalyticDB for MySQL stores data using relational models. It can also use SQL to compute and analyze data. AnalyticDB for MySQL allows you to manage your databases, scale in and out nodes, scale up or down instances, and more. It offers various visualization and ETL tools that make data processing in enterprises easier. Instant multidimensional analysis of large data sets.

Delta Lake is an open-source storage platform that allows ACID transactions to Apache Spark™, and other big data workloads. Data lakes often have multiple data pipelines that read and write data simultaneously. This makes it difficult for data engineers to ensure data integrity due to the absence of transactions. Your data lakes will benefit from ACID transactions with Delta Lake. It offers serializability, which is the highest level of isolation. Learn more at Diving into Delta Lake - Unpacking the Transaction log. Even metadata can be considered "big data" in big data. Delta Lake treats metadata the same as data and uses Spark's distributed processing power for all its metadata. Delta Lake is able to handle large tables with billions upon billions of files and partitions at a petabyte scale. Delta Lake allows developers to access snapshots of data, allowing them to revert to earlier versions for audits, rollbacks, or to reproduce experiments.

Panoply makes it easy to store, sync and access all your business information in the cloud. With built-in integrations to all major CRMs and file systems, building a single source of truth for your data has never been easier. Panoply is quick to set up and requires no ongoing maintenance. It also offers award-winning support, and a plan to fit any need.

Oracle Autonomous Data Warehouse, a cloud-based data warehouse service, eliminates the complexity of operating a data warehouse, data warehouse center, or dw cloud. It also makes it easy to secure data and develop data-driven apps. It automates provisioning and tuning, scaling, security, tuning, scaling, as well as backing up the data warehouse. It provides tools for self-service data loading and data transformations, business models and automatic insights. There are also built-in converged databases capabilities that allow for simpler queries across multiple types of data and machine learning analysis. It is available in both the Oracle cloud public and customers' data centers using Oracle Cloud@Customer. DSC, an industry expert, has provided a detailed analysis that demonstrates why Oracle Autonomous Data Warehouse is a better choice for most global organizations. Find out about compatible applications and tools with Autonomous Data Warehouse.

A data model for the industry from IBM is a blueprint that combines best practices, government regulations, and the complex data analysis needs of the industry. A model can help manage data lakes and data warehouses to gain deeper insights that will allow you to make better decisions. These models include business terminology, warehouse design models, and business intelligence templates. This framework is designed for specific industry-specific organizations to help you accelerate your analytics journey. Industry-specific information infrastructures make it easier to analyze and design functional requirements. To model changing requirements, create and rationalize data warehouses with a consistent architecture. To accelerate transformation, reduce risk and deliver better data to all apps. Establish enterprise-wide KPIs to address compliance, reporting, and analysis requirements. To govern your data, use industry data model vocabulary and templates for regulatory reporting.

GeoSpock DB - The space-time analytics database - allows data fusion in the connected world. GeoSpockDB is a unique cloud-native database that can be used to query for real-world applications. It can combine multiple sources of Internet of Things data to unlock their full potential, while simultaneously reducing complexity, cost, and complexity. GeoSpock DB enables data fusion and efficient storage. It also allows you to run ANSI SQL query and connect to analytics tools using JDBC/ODBC connectors. Users can perform analysis and share insights with familiar toolsets. This includes support for common BI tools such as Tableau™, Amazon QuickSight™, and Microsoft Power BI™, as well as Data Science and Machine Learning environments (including Python Notebooks or Apache Spark). The database can be integrated with internal applications as well as web services, including compatibility with open-source visualisation libraries like Cesium.js and Kepler.

DashDB Local is the newest edition of the IBM dashDB family. It provides organizations with the most flexible architecture to lower the cost of analytics in the dynamic worlds of big data and cloud. How is this possible? Analytics workloads can be easily moved and optimized by a common engine with different deployment options across public and private clouds. DashDB Local is an option if you prefer to deploy on a hosted private clouds or on-premises private clouds through a software defined infrastructure. DashDB Local is easy to deploy and manage from an IT perspective. It uses container technology with elastic scaling and simple maintenance. DashDB Local is user-friendly. It provides the speed to cycle through data acquisition, apply the right analytics to meet a particular use case, and then operationalizes the insights.

Databend is an agile, cloud-native, modern data warehouse that delivers high-performance analytics at a low cost for large-scale data processing. It has an elastic architecture which scales dynamically in order to meet the needs of different workloads. This ensures efficient resource utilization and lower operating costs. Databend, written in Rust offers exceptional performance thanks to features such as vectorized query execution, columnar storage and optimized data retrieval and processing speed. Its cloud-first approach allows for seamless integration with cloud platforms and emphasizes reliability, consistency of data, and fault tolerance. Databend is a free and open-source solution that makes it an accessible and flexible choice for data teams who want to handle big data analysis in the cloud.

With your own data shop, create new revenue streams from the data you already have. Narrative focuses on the fundamental principles that make buying or selling data simpler, safer, and more strategic. You must ensure that the data you have access to meets your standards. It is important to know who and how the data was collected. Access new supply and demand easily for a more agile, accessible data strategy. You can control your entire data strategy with full end-to-end access to all inputs and outputs. Our platform automates the most labor-intensive and time-consuming aspects of data acquisition so that you can access new data sources in days instead of months. You'll only ever have to pay for what you need with filters, budget controls and automatic deduplication.

VeloDB, powered by Apache Doris is a modern database for real-time analytics at scale. In seconds, micro-batch data can be ingested using a push-based system. Storage engine with upserts, appends and pre-aggregations in real-time. Unmatched performance in real-time data service and interactive ad hoc queries. Not only structured data, but also semi-structured. Not only real-time analytics, but also batch processing. Not only run queries against internal data, but also work as an federated query engine to access external databases and data lakes. Distributed design to support linear scalability. Resource usage can be adjusted flexibly to meet workload requirements, whether on-premise or cloud deployment, separation or integration. Apache Doris is fully compatible and built on this open source software. Support MySQL functions, protocol, and SQL to allow easy integration with other tools.

Qubole is an open, secure, and simple Data Lake Platform that enables machine learning, streaming, or ad-hoc analysis. Our platform offers end-to-end services to reduce the time and effort needed to run Data pipelines and Streaming Analytics workloads on any cloud. Qubole is the only platform that offers more flexibility and openness for data workloads, while also lowering cloud data lake costs up to 50%. Qubole provides faster access to trusted, secure and reliable datasets of structured and unstructured data. This is useful for Machine Learning and Analytics. Users can efficiently perform ETL, analytics, or AI/ML workloads in an end-to-end fashion using best-of-breed engines, multiple formats and libraries, as well as languages that are adapted to data volume and variety, SLAs, and organizational policies.

Utilihive, a cloud-native big-data integration platform, is offered as a managed (SaaS) service. Utilihive, the most popular Enterprise-iPaaS (iPaaS), is specifically designed for utility and energy usage scenarios. Utilihive offers both the technical infrastructure platform (connectivity and integration, data ingestion and data lake management) and preconfigured integration content or accelerators. (connectors and data flows, orchestrations and utility data model, energy services, monitoring and reporting dashboards). This allows for faster delivery of data-driven services and simplifies operations.

Create data products in seconds from any source, without moving data. You can make them available to anyone while still maintaining total control. Deliver powerful experiences to unlock the value. Enhance your data mesh through seamless sharing, discovery, and governance of data across domains. Unified access to high-quality products will accelerate innovation and foster collaboration. Access AI models for all users. Control the way data interacts with AI in order to protect intellectual property. Automate AI workflows for rapid integration and iteration of new capabilities. Snowflake allows you to access and build data products without having to move any data. Enjoy the ease of getting even more out of your data. Allow anyone to easily analyze data, and eliminate the need for central provisioning of infrastructure and software. Data products are seamlessly integrated with tools to ensure governance and speed up outcomes.

Many customers of Amazon Web Services (AWS), require data storage and analytics solutions that are more flexible and agile than traditional data management systems. Data lakes are a popular way to store and analyze data. They allow companies to manage multiple data types, from many sources, and store these data in a central repository. AWS Cloud offers many building blocks to enable customers to create a secure, flexible, cost-effective data lake. These services include AWS managed services that allow you to ingest, store and find structured and unstructured data. AWS offers the data solution to support customers in building data lakes. This is an automated reference implementation that deploys an efficient, cost-effective, high-availability data lake architecture on AWS Cloud. It also includes a user-friendly console for searching for and requesting data.

Big data is essential for solving today's industry and enterprise problems. The ability to capture data from across your enterprise--whether generated by disparate applications, people, or IoT infrastructure-offers tremendous potential. Data Lake tools from Infor provide schema-on-read intelligence and a flexible data consumption framework that enables new ways to make key decisions. You can use leveraged access to all of your Infor ecosystem to start capturing and delivering large data to power your next generation machine learning and analytics strategies. The Infor Data Lake is infinitely scalable and provides a central repository for all your enterprise data. You can grow with your insights and investments, ingest additional content for better informed decision making, improve your analytics profiles and provide rich data sets that will enable you to build more powerful machine-learning processes.

A data lake is a central repository for big data and AI computing. It allows you to store both structured and unstructured data at any size. Data Lake Formation (DLF), is a key component in the cloud-native database lake framework. DLF is a simple way to create a cloud-native database lake. It integrates seamlessly with a variety compute engines. You can manage metadata in data lakes in an centralized manner and control enterprise class permissions. It can systematically collect structured, semi-structured and unstructured data, and supports massive data storage. This architecture separates storage and computing. This allows you to plan resources on demand and at low costs. This increases data processing efficiency to meet rapidly changing business needs. DLF can automatically detect and collect metadata from multiple engines. It can also manage the metadata in a central manner to resolve data silo problems.

Kylo is an enterprise-ready open-source data lake management platform platform for self-service data ingestion and data preparation. It integrates metadata management, governance, security, and best practices based on Think Big's 150+ big-data implementation projects. Self-service data ingest that includes data validation, data cleansing, and automatic profiling. Visual sql and an interactive transformation through a simple user interface allow you to manage data. Search and explore data and metadata. View lineage and profile statistics. Monitor the health of feeds, services, and data lakes. Track SLAs and troubleshoot performance. To enable user self-service, create batch or streaming pipeline templates in Apache NiFi. While organizations can spend a lot of engineering effort to move data into Hadoop, they often struggle with data governance and data quality. Kylo simplifies data ingest and shifts it to data owners via a simple, guided UI.

Automate your Data Science. Create data automation workflows. You can design on your desktop and run it anywhere. Modern data integration tool. Tweakstreet can be installed on your computer. It is not a service. You have complete control over your data. You can design a desktop app that you can run anywhere, including your desktop, cloud servers, or data centers. Connect to everything. Tweakstreet provides connectors for common data sources like file formats, databases, online services, and more. We are constantly adding connectors to new releases. File formats. Support for common data exchange formats like CSV, XML and JSON is available out of the box. SQL databases. You can use popular SQL databases such as Postgres, MariaDB and SQL Server, Oracle, MySQL or DB2. Tweakstreet also offers generic support for any database with JDBC drivers. Tweakstreet Web APIs supports HTTP interfaces, such as REST-style APIs. Access to popular APIs is made possible by OAuth 2.0 authentication.

Palo Alto Networks solutions can be enabled by integrating security data from your enterprise. Rapidly simplify security operations by integrating, transforming, and collecting your enterprise's security information. Access to rich data at cloud native scale enables AI and machine learning. Using trillions of multi-source artifacts, you can significantly improve detection accuracy. Cortex XDR™, the industry's leading prevention, detection, response platform, runs on fully integrated network, endpoint, and cloud data. Prisma™, Access protects applications, remote networks, and mobile users in a consistent way, no matter where they are. All users can access all applications via a cloud-delivered architecture, regardless of whether they are at headquarters, branch offices, or on the road. Combining Panorama™, Cortex™, and Data Lake management creates an affordable, cloud-based log solution for Palo Alto Networks Next-Generation Firewalls. Cloud scale, zero hardware, available anywhere.

IBM Storage Scale, a software-defined object and file storage, allows organizations to build global data platforms for artificial intelligence (AI), advanced analytics and high-performance computing. Unlike traditional applications that work with structured data, today's performance-intensive AI and analytics workloads operate on unstructured data, such as documents, audio, images, videos, and other objects. IBM Storage Scale provides global data abstractions services that seamlessly connect data sources in multiple locations, even non-IBM storage environments. It is based on a massively-parallel file system that can be deployed across multiple hardware platforms, including x86 and IBM Power mainframes as well as ARM-based POSIX clients, virtual machines and Kubernetes.

End-to-end DataOps built upon an agile platform that protects and improves your data assets. Arena is the leading augmented data management platform. Our active data catalog allows for self-service data enrichment to control complex data environments. You can create custom workflows to increase the reliability and accuracy of each data set. Machine-learning can be used to identify and align master assets for better data decisions. Superior security is assured with complete lineage, including detailed visualizations and masking. Data management is easy with Arena. Arena can catalog your data from any location. Our extensible connections allow for analytics across all your preferred tools. Overcome data sprawl challenges with our software. Our software is designed to drive business and analytics success, while also providing the controls and extensibility required in today's multicloud data complexity.

Storage that does not lock data in. Managed data lakes allow you to get up and running quickly. You don't need to be a data expert to store, retrieve, and access data. Cribl Lake prevents you from drowning in information. Store, manage, enforce policies on data, and access it when you need to. Open formats and unified policies for retention, security and access control will help you to embrace the future. Let Cribl do the heavy lifting to make data usable and valuable for the teams and tools who need it. Cribl Lake allows you to be up and running in minutes, not months. Zero configuration thanks to automated provisioning and pre-built integrations. Streamline workflows using Stream and Edge to streamline data ingestion and routing. Cribl Search allows you to get the most out of your data, no matter where it is stored. You can easily collect and store your data for long-term storage. Define specific retention periods to comply with legal and business requirements.

IBM®, Db2®, Warehouse is a client-managed preconfigured data warehouse that runs on private clouds, virtual private cloud, and other container-supported infrastructures. It is the ideal hybrid cloud solution for those who need to retain control over their data, but still want cloud-like flexibility. Db2 Warehouse allows you to bring AI into your business faster and more easily with built-in machine-learning, automated scaling, and built-in analytics. You can deploy a pre-configured data store in minutes on any supported infrastructure. Elastic scaling allows for easy updates and upgrades. Enterprise AI can operate faster and more efficiently by applying in-database analytics to the data. Your application can be written once and moved to the correct location -- public cloud, private cloud, or on-premises -- with minimal changes.

Apache Kylin™, an open-source distributed Analytical Data Warehouse (Big Data), was created to provide OLAP (Online Analytical Processing), in this big data era. Kylin can query at near constant speed regardless of increasing data volumes by renovating the multi-dimensional cube, precalculation technology on Hadoop or Spark, and thereby achieving almost constant query speed. Kylin reduces query latency from minutes down to a fraction of a second, bringing online analytics back into big data. Kylin can analyze more than 10+ billion rows in less time than a second. No more waiting for reports to make critical decisions. Kylin connects Hadoop data to BI tools such as Tableau, PowerBI/Excel and MSTR. This makes Hadoop BI faster than ever. Kylin is an Analytical Data Warehouse and offers ANSI SQL on Hadoop/Spark. It also supports most ANSI SQL queries functions. Because of the low resource consumption for each query, Kylin can support thousands upon thousands of interactive queries simultaneously.

Apache Druid, an open-source distributed data store, is Apache Druid. Druid's core design blends ideas from data warehouses and timeseries databases to create a high-performance real-time analytics database that can be used for a wide range of purposes. Druid combines key characteristics from each of these systems into its ingestion, storage format, querying, and core architecture. Druid compresses and stores each column separately, so it only needs to read the ones that are needed for a specific query. This allows for fast scans, ranking, groupBys, and groupBys. Druid creates indexes that are inverted for string values to allow for fast search and filter. Connectors out-of-the box for Apache Kafka and HDFS, AWS S3, stream processors, and many more. Druid intelligently divides data based upon time. Time-based queries are much faster than traditional databases. Druid automatically balances servers as you add or remove servers. Fault-tolerant architecture allows for server failures to be avoided.

Our unified cloud solution for data and analytics enables business users to connect data with business contexts and unlock insights. SAP Data Warehouse Cloud unites data and analytics in a cloud platform that includes data integration, data warehouse, data warehouse, as well as analytics capabilities. This will help you unleash your data-driven enterprise. Built on the SAP HANA Cloud database, this software-as-a-service (SaaS) empowers you to better understand your business data and make confident decisions based on real-time information. You can connect data across multi-cloud and local repositories in real time, while keeping the context of your business. SAP HANA Cloud enables you to gain insights and analyze real-time data at lightning speed. All users can access self-service capabilities to connect, model and visualize their data securely in an IT-governed environment. Use pre-built templates, data models, and industry content.

A data virtualization solution for enterprise data that allows access to multiple data sources and delivers the data and IT-curated data services foundation needed for almost any solution. The TIBCO®, Data Virtualization system is a modern data layer that addresses the changing needs of companies with mature architectures. Eliminate bottlenecks, enable consistency and reuse, and provide all data on demand in a single logical level that is governed, secure and serves a diverse user community. You can access all data immediately to develop actionable insights and take immediate action. Users feel empowered because they can search and select from a self service directory of virtualized business information and then use their favorite analytical tools to get results. They can spend more time analysing data and less time searching.

Palo helps enterprises create the PB level MPP architecture data warehouse services in just a few minutes and import massive data from RDS BOS and BMR. Palo is able to perform multi-dimensional analysis of big data. Palo is compatible to mainstream BI tools. Data analysts can quickly gain insights by analyzing and displaying the data visually. It has an industry-leading MPP engine with column storage, intelligent indexes, and vector execution functions. It can also provide advanced analytics, window functions and in-library analytics. You can create a materialized table and change its structure without suspending service. It supports flexible data recovery.