Alternatives to Ocient Hyperscale Data Warehouse

ANSI SQL allows you to analyze petabytes worth of data at lightning-fast speeds with no operational overhead. Analytics at scale with 26%-34% less three-year TCO than cloud-based data warehouse alternatives. You can unleash your insights with a trusted platform that is more secure and scales with you. Multi-cloud analytics solutions that allow you to gain insights from all types of data. You can query streaming data in real-time and get the most current information about all your business processes. Machine learning is built-in and allows you to predict business outcomes quickly without having to move data. With just a few clicks, you can securely access and share the analytical insights within your organization. Easy creation of stunning dashboards and reports using popular business intelligence tools right out of the box. BigQuery's strong security, governance, and reliability controls ensure high availability and a 99.9% uptime SLA. Encrypt your data by default and with customer-managed encryption keys

Smart Software, a leading provider in demand planning, inventory optimization, and supply chain analytics solutions, is based in Belmont, Massachusetts USA. Smart Software was founded in 1981 and has helped thousands of customers plan for future demands using industry-leading statistical analysis. Smart Inventory Planning & Optimization is the company's next generation suite of native web apps. It helps inventory-carrying organizations reduce inventory, improve service levels, and streamline Sales, Inventory, Operations Planning. Smart IP&O is a Digital Supply Chain Platform that hosts three applications: dashboard reporting, inventory optimization, demand planning. Smart IP&O acts as an extension to our customers' ERP systems. It receives daily transaction data, returns forecasts and stock policy values to drive replenishment planning and production planning.

Improvado, an ETL solution, facilitates data pipeline automation for marketing departments without any technical skills. This platform supports marketers in making data-driven, informed decisions. It provides a comprehensive solution for integrating marketing data across an organization. Improvado extracts data form a marketing data source, normalizes it and seamlessly loads it into a marketing dashboard. It currently has over 200 pre-built connectors. On request, the Improvado team will create new connectors for clients. Improvado allows marketers to consolidate all their marketing data in one place, gain better insight into their performance across channels, analyze attribution models, and obtain accurate ROMI data. Companies such as Asus, BayCare and Monster Energy use Improvado to mark their markes.

Actian Avalanche, a fully managed hybrid cloud service for data warehouse, is designed from the ground up in order to deliver high performance across all dimensions (data volume, concurrent users, and query complexity) at a fraction the cost of other solutions. It is a hybrid platform that can be deployed both on-premises and on multiple clouds including AWS Azure, Google Cloud, and Azure. This allows you to migrate and offload data to the cloud at your pace. Actian Avalanche offers the best price-performance ratio in the industry without the need for optimization or DBA tuning. You can get substantially better performance at a fraction of the cost of other solutions or choose the same performance at a significantly lower price. Avalanche, for example, offers up to 6x the price-performance advantages over Snowflake according to GigaOm’s TPC-H industry benchmark and more than many other appliance vendors.

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.

100% compatible with Netezza Upgrade via a single command-line line. Available on premises, in the cloud, or hybrid. IBM®, Netezza®, Performance Server for IBM Cloud Pack® Data is an advanced data warehouse platform and analytics platform that is available on premises or on the cloud. This next generation of Netezza includes enhancements to the in-database analytics capabilities. You can do data science and machinelearning with data volumes scaling to the petabytes. Fast failure recovery and failure detection. Upgrade existing systems with a single command-line command. Ability to query multiple systems simultaneously. Select the nearest availability zone or data center, select the required number of compute units, and then go. IBM®, Netezza®, Performance Server for IBM Cloud® for Data is available via Amazon Web Services, Microsoft Azure, and IBM Cloud®. Netezza can be deployed on a private cloud using IBM Cloud Pak Data System.

Instead of getting bogged down in data warehouse code, keep your eyes on the important and compelling reporting, analytics, and insights. Your data warehouse should not become a mess of hundreds of unmanageable stored procedures, notebooks, stored processes, tables, and other complicated pieces. Views and other information. The effort required to design, build and manage a data warehouse is dramatically reduced with Dimodelo DW Studio. You can design, build, and deploy a data warehouse that targets Azure Synapse Analytics. Dimodelo Data Warehouse Studio creates a best-practice architecture using Azure Data Lake, Polybase, and Azure Synapse Analytics. This results in a modern, high-performance data warehouse in the cloud. Dimodelo Data Warehouse Studio creates a best-practice architecture that delivers a modern, high-performance data warehouse in the cloud by using parallel bulk loads and in memory tables.

The Unified Analytics Warehouse. The Unified Analytics Warehouse is the best place to find high-performing analytics and machine learning at large scale. Tech research analysts are seeing new leaders as they strive to deliver game-changing big data analytics. Vertica empowers data-driven companies so they can make the most of their analytics initiatives. It offers advanced time-series, geospatial, and machine learning capabilities, as well as data lake integration, user-definable extensions, cloud-optimized architecture and more. Vertica's Under the Hood webcast series allows you to dive into the features of Vertica - delivered by Vertica engineers, technical experts, and others - and discover what makes it the most scalable and scalable advanced analytical data database on the market. Vertica supports the most data-driven disruptors around the globe in their pursuit for industry and business transformation.

Rapidly create your own DWH. Quickly create your own DWH and start creating reports. The Datavault Builder, a 4th generation Data Warehouse automation software, covers all phases and aspects of a DWH. You can quickly set up your agile Data Warehouse and start delivering business value within the first sprint by following a standard industry process. Merger&Acquisitions and affiliated companies, sales performance, and supply chain management. Data integration is crucial in all of these cases, and many others. These settings are perfectly supported by Datavault Builder. This tool is not only a tool but a standard workflow.

Snowflake®, a cloud data platform and enterprise-grade architecture, allows you to securely store and use your data in the cloud. Drag-and-drop visual workflow design and built-in ETL to connect, clean and transform data from 250+ sources. You can generate actionable insights and insights from your data using the latest Search and AI-driven technology. Our AI/ML environments can be used to build, tune, and deploy models for predictive analytics or forecasting. Our AI/ML environments are available to help you take your data to new heights. The PurpleCube Data Science module allows you to create, train, tune, and deploy AI models for forecasting and predictive analysis. PurpleCube Analytics allows you to create BI visualizations, search your data with natural language and use AI-driven insights and smart recommendations to provide answers to questions that you didn't know to ask.

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.

Apache Doris is an advanced data warehouse for real time analytics. It delivers lightning fast analytics on real-time, large-scale data. Ingestion of micro-batch data and streaming data within a second. Storage engine with upserts, appends and pre-aggregations in real-time. Optimize for high-concurrency, high-throughput queries using columnar storage engine, cost-based query optimizer, and vectorized execution engine. Federated querying for data lakes like Hive, Iceberg, and Hudi and databases like MySQL and PostgreSQL. Compound data types, such as Arrays, Maps and JSON. Variant data types to support auto datatype inference for JSON data. NGram bloomfilter for text search. Distributed design for linear scaling. Workload isolation, tiered storage and efficient resource management. Supports shared-nothing as well as the separation of storage from compute.

SAP BW/4HANA, a packaged data warehouse that uses SAP HANA, is an example of a packaged data warehouse. It is the on-premise data warehouse layer for SAP's Business Technology Platform. It allows you to consolidate data across your enterprise to get a consistent, agreed upon view of your data. Streamline your processes and support innovation with one source for real-time insight. Our next-generation SAP HANA-based data warehouse solution will help you maximize the value of all your data, whether it is from SAP applications or third party solutions. It also supports unstructured, geospatial or Hadoop-based data. Transform data practices to increase efficiency and agility in the deployment of live insights at scale on premise and in the cloud. A Big Data warehouse can be used to drive digitization across all business lines, and it also allows you to leverage digital business platform solutions from SAP.

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.

Firebolt solves impossible data problems with extreme speed and elasticity on any scale. Firebolt has completely redesigned its cloud data warehouse to provide an extremely fast and efficient analytics experience at all scales. You can analyze more data at higher levels of detail with lightning fast queries, which is an order-of-magnitude improvement in performance. You can easily scale up or decrease to support any workload, data amount, and concurrent users. Firebolt believes data warehouses should be easier than we are used to. We strive to make everything that was previously difficult and labor-intensive, simple. Cloud data warehouse providers make money from the cloud resources that you use. We don't! Finally, a pricing system that is fair, transparent, and allows for scale without breaking the bank.

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.

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.

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.

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.

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.

SelectDB is an advanced data warehouse built on Apache Doris. It supports rapid query analysis of large-scale, real-time data. Clickhouse to Apache Doris to separate the lake warehouse, and upgrade the lake storage. Fast-hand OLAP system carries out nearly 1 billion queries every day in order to provide data services for various scenes. The original lake warehouse separation was abandoned due to problems with storage redundancy and resource seizure. Also, it was difficult to query and adjust. It was decided to use Apache Doris lakewarehouse, along with Doris's materialized views rewriting capability and automated services to achieve high-performance query and flexible governance. Write real-time data within seconds and synchronize data from databases and streams. Data storage engine with real-time update and addition, as well as real-time polymerization.

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.

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.

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.

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.

Data warehouse automation is now faster. Vaultspeed is based on the Data Vault 2.0 standard, a decade of data integration experience, and the Vaultspeed automation tool. All Data Vault 2.0 objects are supported and available for implementation. Generate quality code fast for all scenarios in a Data Vault 2.0 integration system. Vaultspeed can be integrated into your existing setup to maximize your investment in knowledge and tools. You will be in compliance with the Data Vault 2.0 standard. Scalefree is our constant partner. Data Vault 2.0 models are stripped down to the bare essentials so that they can be loaded using the same loading pattern (repeatable) and have the same database structure. Vaultspeed uses a template system that understands the object types and allows for easy-to-set configuration parameters.

Blendo is the most popular ETL and ELT data connector tool that dramatically simplifies how you connect data sources with databases. Blendo supports natively-built data connections, making it easy to extract, load and transform (ETL). Automate data management and transform data faster to gain BI insights. Data analysis does not have to be about data warehousing or data management. Automate and sync data from any SaaS app into your data warehouse. Connect to any data source using ready-made connectors. It's as easy as logging in and your data will start syncing immediately. There are no more integrations to create, data to export, or scripts to create. You can save time and gain insights into your business. You can accelerate your exploration and insights time with reliable data, analytical-ready tables, and schemas that can be optimized for analysis with any BI tool.

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.

A cloud database that can scale to handle large streaming data sets. Kinetica harnesses modern vectorized processors to perform orders of magnitude faster for real-time spatial or temporal workloads. In real-time, track and gain intelligence from billions upon billions of moving objects. Vectorization unlocks new levels in performance for analytics on spatial or time series data at large scale. You can query and ingest simultaneously to take action on real-time events. Kinetica's lockless architecture allows for distributed ingestion, which means data is always available to be accessed as soon as it arrives. Vectorized processing allows you to do more with fewer resources. More power means simpler data structures which can be stored more efficiently, which in turn allows you to spend less time engineering your data. Vectorized processing allows for incredibly fast analytics and detailed visualizations of moving objects at large scale.

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.

We make BI and Big Data analytics easier and more efficient. Our goal is to empower business users, make BI specialists and always-busy business more independent when solving data-driven business problems. Querona is a solution for those who have ever been frustrated by a lack in data, slow or tedious report generation, or a long queue to their BI specialist. Querona has a built-in Big Data engine that can handle increasing data volumes. Repeatable queries can be stored and calculated in advance. Querona automatically suggests improvements to queries, making optimization easier. Querona empowers data scientists and business analysts by giving them self-service. They can quickly create and prototype data models, add data sources, optimize queries, and dig into raw data. It is possible to use less IT. Users can now access live data regardless of where it is stored. Querona can cache data if databases are too busy to query live.

Materialize is a reactive database that provides incremental view updates. Our standard SQL allows developers to easily work with streaming data. Materialize connects to many external data sources without any pre-processing. Connect directly to streaming sources such as Kafka, Postgres databases and CDC or historical data sources such as files or S3. Materialize allows you to query, join, and transform data sources in standard SQL - and presents the results as incrementally-updated Materialized views. Queries are kept current and updated as new data streams are added. With incrementally-updated views, developers can easily build data visualizations or real-time applications. It is as easy as writing a few lines SQL to build with streaming data.

MaxCompute, formerly known as ODPS, is a multi-tenant, general-purpose data processing platform that can be used for large-scale data warehousing. MaxCompute supports a variety of data importing options and distributed computing models. This allows users to query large datasets efficiently, reduce production costs, and ensure data safety. Supports EB-level data storage. Supports SQL, MapReduce and Graph computational models as well as Message Passing Interface (MPI), iterative algorithms. This cloud is more efficient than an enterprise private cloud and offers storage and computing services that are up to 20% to 30% cheaper. Stable offline analysis services that last more than seven years. Also, multi-level sandbox protection is possible. Monitoring and monitoring are possible. MaxCompute uses tunnels for data transmission. Tunnels can be scaled and used to import and export PB-level data daily. Multiple tunnels allow you to import all data and history data.

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.

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.

QuerySurge is the smart Data Testing solution that automates the data validation and ETL testing of Big Data, Data Warehouses, Business Intelligence Reports and Enterprise Applications with full DevOps functionality for continuous testing. Use Cases - Data Warehouse & ETL Testing - Big Data (Hadoop & NoSQL) Testing - DevOps for Data / Continuous Testing - Data Migration Testing - BI Report Testing - Enterprise Application/ERP Testing Features Supported Technologies - 200+ data stores are supported QuerySurge Projects - multi-project support Data Analytics Dashboard - provides insight into your data Query Wizard - no programming required Design Library - take total control of your custom test desig BI Tester - automated business report testing Scheduling - run now, periodically or at a set time Run Dashboard - analyze test runs in real-time Reports - 100s of reports API - full RESTful API DevOps for Data - integrates into your CI/CD pipeline Test Management Integration QuerySurge will help you: - Continuously detect data issues in the delivery pipeline - Dramatically increase data validation coverage - Leverage analytics to optimize your critical data - Improve your data quality at speed

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.

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.

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

biGENIUS automates all phases of analytic data management solutions (e.g. data warehouses, data lakes and data marts. thereby allowing you to turn your data into a business as quickly and cost-effectively as possible. Your data analytics solutions will save you time, effort and money. Easy integration of new ideas and data into data analytics solutions. The metadata-driven approach allows you to take advantage of new technologies. Advancement of digitalization requires traditional data warehouses (DWH) as well as business intelligence systems to harness an increasing amount of data. Analytical data management is essential to support business decision making today. It must integrate new data sources, support new technologies, and deliver effective solutions faster than ever, ideally with limited resources.

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.

Hologres, a cloud-native Hybrid Serving & Analytical Processing system (HSAP), is seamlessly integrated into the big data ecosystem. Hologres can be used to process PB-scale data at high concurrency with low latency. Hologres allows you to use your business intelligence (BI), tools to analyze data in multiple dimensions. You can also explore your business in real time. Hologres eliminates data silos and redundancy that are disadvantages of traditional real time data warehousing systems. It can be used to migrate large amounts of data and perform real-time analysis. It responds to queries on PB scale data at sub-second speeds. This speed allows you to quickly analyze data in multiple dimensions and examine your business in real time. Supports concurrent writes and queries at speeds up to 100,000,000 transactions per second (TPS). Data can be accessed immediately after it has been written.

Connect and centralize data. Transform your data landscape into a flexible powerhouse. Data Virtuality is a data integration platform that allows for instant data access, data centralization, and data governance. Logical Data Warehouse combines materialization and virtualization to provide the best performance. For high data quality, governance, and speed-to-market, create your single source data truth by adding a virtual layer to your existing data environment. Hosted on-premises or in the cloud. Data Virtuality offers three modules: Pipes Professional, Pipes Professional, or Logical Data Warehouse. You can cut down on development time up to 80% Access any data in seconds and automate data workflows with SQL. Rapid BI Prototyping allows for a significantly faster time to market. Data quality is essential for consistent, accurate, and complete data. Metadata repositories can be used to improve master data management.

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.

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.

Dapps built on top Space and Time are blockchain interoperable. They crunch SQL + machine learning for Gaming/DeFi as well as any other decentralized applications that require verifiable tamperproofing or blockchain-security. By connecting off-chain storage to on-chain analytics insights, we merge blockchain data with a new-generation database. Multi-chain integration, indexing and anchoring are made easy by combining on-chain and offline data. Advanced data security with proven capabilities. Connect to real-time, relational blockchain data that we have already indexed from major chain data sources as well as data you have ingested off-chain. You can send tamperproof query results to smart contract in a trustless manner or publish the query results directly onto-chain using our cryptographic guarantees (Proof SQL).

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.

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.

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.

Bi(OS)®, a single platform that provides unparalleled speed and insight for data app developers, enables them to build apps in a more unified way. The entire life-cycle of building data applications takes just hours to complete with bi(OS®. This includes adding diverse data sources, generating real-time insights and deploying to production. Join enterprise data teams from across industries to become the data superhero that your business needs. The promised data-driven impact of Open Source, Cloud, or SaaS has not been realized by the trio of Open Source, Cloud, or SaaS. All the investments made by enterprises have been in data integration and movement, which is not sustainable. A new approach to data is needed that is enterprise-focused. Bi(OS)®, is a reimagining of the first principles of enterprise data management, from ingest through insight. It supports API, AI, BI builders and other unified functions to deliver data-driven impact in days. Engineers create an enduring moat when a symphony between IT teams, tools and processes emerges.