Alternatives to Space and Time

BigQuery is a serverless, multicloud data warehouse that makes working with all types of data effortless, allowing you to focus on extracting valuable business insights quickly. As a central component of Google’s data cloud, it streamlines data integration, enables cost-effective and secure scaling of analytics, and offers built-in business intelligence for sharing detailed data insights. With a simple SQL interface, it also supports training and deploying machine learning models, helping to foster data-driven decision-making across your organization. Its robust performance ensures that businesses can handle increasing data volumes with minimal effort, scaling to meet the needs of growing enterprises. Gemini within BigQuery brings AI-powered tools that enhance collaboration and productivity, such as code recommendations, visual data preparation, and intelligent suggestions aimed at improving efficiency and lowering costs. The platform offers an all-in-one environment with SQL, a notebook, and a natural language-based canvas interface, catering to data professionals of all skill levels. This cohesive workspace simplifies the entire analytics journey, enabling teams to work faster and more efficiently.

ClicData is the first cloud-based 100% cloud-based Business Intelligence software and data management software. Our data warehouse makes it easy to combine, transform, and merge data from any source. You can create interactive dashboards that are self-updated and shareable with your manager, team, or customers in multiple ways. Email delivery schedule, export, or dynamic dashboards via LiveLinks. ClicData automates everything, including data connection, data refresh, management, and scheduling routines.

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.

Apache Doris serves as a cutting-edge data warehouse tailored for real-time analytics, enabling exceptionally rapid analysis of data at scale. It features both push-based micro-batch and pull-based streaming data ingestion that occurs within a second, alongside a storage engine capable of real-time upserts, appends, and pre-aggregation. With its columnar storage architecture, MPP design, cost-based query optimization, and vectorized execution engine, it is optimized for handling high-concurrency and high-throughput queries efficiently. Moreover, it allows for federated querying across various data lakes, including Hive, Iceberg, and Hudi, as well as relational databases such as MySQL and PostgreSQL. Doris supports complex data types like Array, Map, and JSON, and includes a Variant data type that facilitates automatic inference for JSON structures, along with advanced text search capabilities through NGram bloomfilters and inverted indexes. Its distributed architecture ensures linear scalability and incorporates workload isolation and tiered storage to enhance resource management. Additionally, it accommodates both shared-nothing clusters and the separation of storage from compute resources, providing flexibility in deployment and management.

Amazon Redshift is the preferred choice among customers for cloud data warehousing, outpacing all competitors in popularity. It supports analytical tasks for a diverse range of organizations, from Fortune 500 companies to emerging startups, facilitating their evolution into large-scale enterprises, as evidenced by Lyft's growth. No other data warehouse simplifies the process of extracting insights from extensive datasets as effectively as Redshift. Users can perform queries on vast amounts of structured and semi-structured data across their operational databases, data lakes, and the data warehouse using standard SQL queries. Moreover, Redshift allows for the seamless saving of query results back to S3 data lakes in open formats like Apache Parquet, enabling further analysis through various analytics services, including Amazon EMR, Amazon Athena, and Amazon SageMaker. Recognized as the fastest cloud data warehouse globally, Redshift continues to enhance its performance year after year. For workloads that demand high performance, the new RA3 instances provide up to three times the performance compared to any other cloud data warehouse available today, ensuring businesses can operate at peak efficiency. This combination of speed and user-friendly features makes Redshift a compelling choice for organizations of all sizes.

Introducing a unique cloud data lakehouse that is entirely managed and capable of ingesting data from all your sources within minutes, while seamlessly accommodating every query engine at scale, all at a significantly reduced cost. This platform enables ingestion from both databases and event streams at terabyte scale in near real-time, offering the ease of fully managed pipelines. Furthermore, you can execute queries using any engine, catering to diverse needs such as business intelligence, real-time analytics, and AI/ML applications. By adopting this solution, you can reduce your expenses by over 50% compared to traditional cloud data warehouses and ETL tools, thanks to straightforward usage-based pricing. Deployment is swift, taking just minutes, without the burden of engineering overhead, thanks to a fully managed and highly optimized cloud service. Consolidate your data into a single source of truth, eliminating the necessity of duplicating data across various warehouses and lakes. Select the appropriate table format for each task, benefitting from seamless interoperability between Apache Hudi, Apache Iceberg, and Delta Lake. Additionally, quickly set up managed pipelines for change data capture (CDC) and streaming ingestion, ensuring that your data architecture is both agile and efficient. This innovative approach not only streamlines your data processes but also enhances decision-making capabilities across your organization.

Apache Druid is a distributed data storage solution that is open source. Its fundamental architecture merges concepts from data warehouses, time series databases, and search technologies to deliver a high-performance analytics database capable of handling a diverse array of applications. By integrating the essential features from these three types of systems, Druid optimizes its ingestion process, storage method, querying capabilities, and overall structure. Each column is stored and compressed separately, allowing the system to access only the relevant columns for a specific query, which enhances speed for scans, rankings, and groupings. Additionally, Druid constructs inverted indexes for string data to facilitate rapid searching and filtering. It also includes pre-built connectors for various platforms such as Apache Kafka, HDFS, and AWS S3, as well as stream processors and others. The system adeptly partitions data over time, making queries based on time significantly quicker than those in conventional databases. Users can easily scale resources by simply adding or removing servers, and Druid will manage the rebalancing automatically. Furthermore, its fault-tolerant design ensures resilience by effectively navigating around any server malfunctions that may occur. This combination of features makes Druid a robust choice for organizations seeking efficient and reliable real-time data analytics solutions.

StarkEx is designed to generate validity proofs, which guarantee that only legitimate data derived from trustworthy computations is recorded on the blockchain. The remarkable scalability of StarkEx stems from the asymmetric workload distribution between its off-chain prover and the on-chain verifier. It supports self-custodial decentralized applications (dApps) and incorporates cutting-edge anti-censorship measures to ensure that users maintain control over their funds at all times. Furthermore, StarkEx has been crafted to accommodate a wide variety of user requirements and application functionalities. Applications seeking to connect with StarkEx can typically launch on the Mainnet within a few weeks, depending on how advanced their off-chain Operator node is. With the implementation of validity proofs, state updates achieve finality as soon as they are confirmed on-chain, which can take just hours, unlike fraud proofs that require a lengthier dispute resolution period. This efficiency not only streamlines the transaction process but also enhances the overall user experience in utilizing blockchain technology.

Experience swift and dependable web3 indexing with our real-time, adaptable blockchain data APIs, featuring no rate limits, minimal latency, and support for multiple chains. Enhance your web3 development journey by gaining effortless access to both on-chain and off-chain data, including cached token media, metadata, and pricing feeds. Investigate complete transaction details, including logs, and query token balances and transactions with ease. Effortlessly search for tokens, collections, and addresses while tailoring data according to your specific indexing patterns. Define contract ABIs and pinpoint events of interest for personalized endpoints, ensuring fast backfill and immediate frontfill capabilities. Our RESTful endpoints are designed to deliver responses in under a second, boasting zero downtime for uninterrupted service. Stay updated by subscribing to on-chain activities you care about and streamline the creation of crypto-enhanced applications in mere seconds with nxyz. Don’t forget to read the documentation and secure your spot on our waitlist to unlock the fastest API available for web3 developers, which is engineered to scale for billions of users while handling millions of queries each second efficiently. This innovative solution could be the key to revolutionizing your interactions with blockchain technology.

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.

Perun is an innovative off-chain framework that facilitates real-time payments along with intricate business logic, enhancing the capabilities of any blockchain. By connecting users across various blockchains, Perun promotes interoperability among different currencies and blockchain networks. This results in instantaneous, energy-efficient, and low-cost transactions, leveraging Layer-2 technology to significantly boost throughput. With the use of virtual channel technology, Perun ensures that transaction data remains private while continually demonstrating robust security measures to uphold advanced procedures. Additionally, Perun enables payments through NFC and Bluetooth, functioning seamlessly even without an active internet connection. A key aspect of Perun’s off-chain framework is its State Channels, which allow users to perform a large volume of transactions off-chain while maintaining security through the underlying blockchain. Furthermore, the integrity of our protocols has been rigorously evaluated using state-of-the-art cryptographic research methods, ensuring the highest standards of reliability and safety. This combination of advanced technology and robust security positions Perun as a leading solution for modern payment needs.

BryteFlow creates remarkably efficient automated analytics environments that redefine data processing. By transforming Amazon S3 into a powerful analytics platform, it skillfully utilizes the AWS ecosystem to provide rapid data delivery. It works seamlessly alongside AWS Lake Formation and automates the Modern Data Architecture, enhancing both performance and productivity. Users can achieve full automation in data ingestion effortlessly through BryteFlow Ingest’s intuitive point-and-click interface, while BryteFlow XL Ingest is particularly effective for the initial ingestion of very large datasets, all without the need for any coding. Moreover, BryteFlow Blend allows users to integrate and transform data from diverse sources such as Oracle, SQL Server, Salesforce, and SAP, preparing it for advanced analytics and machine learning applications. With BryteFlow TruData, the reconciliation process between the source and destination data occurs continuously or at a user-defined frequency, ensuring data integrity. If any discrepancies or missing information arise, users receive timely alerts, enabling them to address issues swiftly, thus maintaining a smooth data flow. This comprehensive suite of tools ensures that businesses can operate with confidence in their data's accuracy and accessibility.

Quickly establish your own Data Warehouse (DWH) to lay the groundwork for new reporting capabilities or seamlessly incorporate emerging data sources with agility, allowing for rapid results. The Datavault Builder serves as a fourth-generation automation tool for Data Warehousing, addressing every aspect and phase of DWH development. By employing a well-established industry-standard methodology, you can initiate your agile Data Warehouse right away and generate business value in the initial sprint. Whether dealing with mergers and acquisitions, related companies, sales performance, or supply chain management, effective data integration remains crucial in these scenarios and beyond. The Datavault Builder adeptly accommodates various contexts, providing not merely a tool but a streamlined and standardized workflow. It enables the retrieval and transfer of data between multiple systems in real-time. Moreover, it allows for the integration of diverse sources, offering a comprehensive view of your organization. As you continually transition data to new targets, the tool ensures both data availability and quality are maintained throughout the process, enhancing your overall operational efficiency. This capability is vital for organizations looking to stay competitive in an ever-evolving market.

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.

Azure Synapse represents the advanced evolution of Azure SQL Data Warehouse. It is a comprehensive analytics service that integrates enterprise data warehousing with Big Data analytics capabilities. Users can query data flexibly, choosing between serverless or provisioned resources, and can do so at scale. By merging these two domains, Azure Synapse offers a cohesive experience for ingesting, preparing, managing, and delivering data, catering to the immediate requirements of business intelligence and machine learning applications. This integration enhances the efficiency and effectiveness of data-driven decision-making processes.

VeloDB, which utilizes Apache Doris, represents a cutting-edge data warehouse designed for rapid analytics on large-scale real-time data. It features both push-based micro-batch and pull-based streaming data ingestion that occurs in mere seconds, alongside a storage engine capable of real-time upserts, appends, and pre-aggregations. The platform delivers exceptional performance for real-time data serving and allows for dynamic interactive ad-hoc queries. VeloDB accommodates not only structured data but also semi-structured formats, supporting both real-time analytics and batch processing capabilities. Moreover, it functions as a federated query engine, enabling seamless access to external data lakes and databases in addition to internal data. The system is designed for distribution, ensuring linear scalability. Users can deploy it on-premises or as a cloud service, allowing for adaptable resource allocation based on workload demands, whether through separation or integration of storage and compute resources. Leveraging the strengths of open-source Apache Doris, VeloDB supports the MySQL protocol and various functions, allowing for straightforward integration with a wide range of data tools, ensuring flexibility and compatibility across different environments.

Palo empowers businesses to swiftly establish a PB-level MPP architecture data warehouse service in just minutes while seamlessly importing vast amounts of data from sources like RDS, BOS, and BMR. This capability enables Palo to execute multi-dimensional big data analytics effectively. Additionally, it integrates smoothly with popular BI tools, allowing data analysts to visualize and interpret data swiftly, thereby facilitating informed decision-making. Featuring a top-tier MPP query engine, Palo utilizes column storage, intelligent indexing, and vector execution to enhance performance. Moreover, it offers in-library analytics, window functions, and a range of advanced analytical features. Users can create materialized views and modify table structures without interrupting services, showcasing its flexibility. Furthermore, Palo ensures efficient data recovery, making it a reliable solution for enterprises looking to optimize their data management processes.

Materialize is an innovative reactive database designed to provide updates to views incrementally. It empowers developers to seamlessly work with streaming data through the use of standard SQL. One of the key advantages of Materialize is its ability to connect directly to a variety of external data sources without the need for pre-processing. Users can link to real-time streaming sources such as Kafka, Postgres databases, and change data capture (CDC), as well as access historical data from files or S3. The platform enables users to execute queries, perform joins, and transform various data sources using standard SQL, presenting the outcomes as incrementally-updated Materialized views. As new data is ingested, queries remain active and are continuously refreshed, allowing developers to create data visualizations or real-time applications with ease. Moreover, constructing applications that utilize streaming data becomes a straightforward task, often requiring just a few lines of SQL code, which significantly enhances productivity. With Materialize, developers can focus on building innovative solutions rather than getting bogged down in complex data management tasks.

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

Actian Avalanche is a hybrid cloud data warehouse service that is fully managed and engineered to achieve exceptional performance and scalability across various aspects, including data volume, the number of concurrent users, and the complexity of queries, all while remaining cost-effective compared to other options. This versatile platform can be implemented on-premises or across several cloud providers like AWS, Azure, and Google Cloud, allowing organizations to transition their applications and data to the cloud at a comfortable rate. With Actian Avalanche, users experience industry-leading price-performance right from the start, eliminating the need for extensive tuning and optimization typically required by database administrators. For the same investment as other solutions, users can either enjoy significantly enhanced performance or maintain comparable performance at a much lower cost. Notably, Avalanche boasts a remarkable price-performance advantage, offering up to 6 times better efficiency than Snowflake, according to GigaOm’s TPC-H benchmark, while outperforming many traditional appliance vendors even further. This makes Actian Avalanche a compelling choice for businesses seeking to optimize their data management strategies.

A comprehensive enterprise data virtualization solution enables seamless access to a variety of data sources while establishing a robust foundation of datasets and IT-managed data services suitable for virtually any application. The TIBCO® Data Virtualization system, functioning as a contemporary data layer, meets the dynamic demands of organizations with evolving architectures. By eliminating bottlenecks, it fosters consistency and facilitates reuse by providing on-demand access to all data through a unified logical layer that is secure, governed, and accessible to a wide range of users. With immediate availability of all necessary data, organizations can derive actionable insights and respond swiftly in real-time. Users benefit from the ability to effortlessly search for and choose from a self-service directory of virtualized business data, utilizing their preferred analytics tools to achieve desired outcomes. This shift allows them to concentrate more on data analysis rather than on the time-consuming task of data retrieval. Furthermore, the streamlined process enhances productivity and enables teams to make informed decisions quickly and effectively.

Truebit serves as an enhancement to blockchain technology, allowing smart contracts to execute intricate computations in conventional programming languages while minimizing gas expenses. Although smart contracts excel at handling minor computations with accuracy, they face significant security vulnerabilities when tasked with larger computations. To address this issue, Truebit introduces a trustless oracle that retrofits existing systems, ensuring the accurate execution of complex tasks. Smart contracts can submit their computation requests to this oracle in the format of WebAssembly bytecode, and in return, anonymous miners earn rewards for providing correct solutions. The protocol of the oracle upholds accuracy through two distinct layers: a unanimous consensus layer that permits anyone to challenge incorrect answers and an on-chain system that motivates engagement and guarantees equitable compensation for participants. The realization of these elements is achieved through an innovative blend of off-chain infrastructure and on-chain smart contracts, thereby enhancing the overall functionality and security of blockchain networks. This dual approach not only improves computational reliability but also fosters a more robust ecosystem for decentralized applications.

Decentralized finance has been facilitated on the Bitcoin network, creating a blockchain focused on delivering swift, intelligent, and transparent financial services that are universally accessible. Transitioning from a trust-based system to a trust-less model, decentralized finance addresses the shortcomings of traditional finance that traditional fintech solutions failed to remedy. Users can engage in a diverse array of crypto-economic financial operations with exceptional transaction throughput, ensuring that all transactions are handled efficiently. Its Turing-incomplete design minimizes potential attack vectors, allowing developers to swiftly build various DeFi applications on a single blockchain. The governance structure is both reliable and decentralized, functioning seamlessly both on and off the chain. The integration with the Bitcoin blockchain ensures immutability and security. Specifically crafted for decentralized finance dApps, users can trade and engage in arbitrage on the decentralized exchange, mine liquidity for yields that can reach up to 100 times, and more—all through the DeFiChain wallet application, which is compatible with Windows, macOS, and Linux platforms. Central to this ecosystem is the $DFI coin, which serves as a vital unit of account within DeFiChain, facilitating a wide range of financial activities and reinforcing the network's overall value proposition.

Ensure that every modification you implement is recorded. Utilize version history to easily switch between iterations, confirming that your API operates without issues. Our infrastructure, optimized for subgraph pre-caching, enables customers to experience indexing speeds that are up to three times faster, all without requiring any code alterations. You can create streams using SQL from subgraphs and other data streams, achieving persistent aggregations with zero latency, accessible through bridges. We offer sub-second, reorganization-aware ETL capabilities to various tools such as Hasura, Timescale, and Elasticsearch, among others. Combine subgraphs from different chains into a single stream, allowing you to perform costly aggregations in just milliseconds. Stack streams on top of one another, integrate with off-chain data, and establish a distinctive real-time perspective of the blockchain. Execute reliable webhooks, conduct analytical queries, and utilize fuzzy search features, among other functionalities. Furthermore, you can connect streams and subgraphs to databases like Timescale and Elasticsearch, or directly to a hosted GraphQL API, expanding your data handling capabilities. This comprehensive approach ensures that your data processing remains efficient and effective.

Create smart contracts utilizing popular software frameworks to make a significant advancement from Solidity into the expansive realm of software tools available on Linux. This transition allows for exceptional computational scalability, enables access to large data files, and ensures minimal transaction fees, all while maintaining the robust security features that Ethereum offers. Whether it’s gaming applications where players' data remains confidential or enterprise solutions handling sensitive information, your decentralized applications can uphold user privacy. Descartes efficiently carries out extensive computational tasks off-chain, leveraging a Linux virtual machine that is entirely governed by a smart contract. The outcomes of these computations can be fully validated and enforced on-chain by reliable Descartes node operators, thus safeguarding the strong security assurances provided by the underlying blockchain. By overcoming Ethereum's scalability constraints, you can achieve computational efficiencies that are magnitudes greater, while still securing the blockchain's strong security standards. This evolution not only enhances user experience but also broadens the potential use cases for decentralized technologies.

Beosin EagleEye offers round-the-clock monitoring and notification services for blockchain security, ensuring that clients receive immediate alerts and warnings about potential threats such as hacking attempts, fraudulent activities, flash loan exploits, and rug pulls by analyzing both on-chain and off-chain data through comprehensive security evaluations. 1. Continuous Monitoring of Blockchain Projects 2. Identification of Risky Transactions, Including Significant Withdrawals, Flash Loans, and Unauthorized Actions 3. Instant Alerts and Warnings for Security Incidents 4. Analysis Utilizing On-chain and Off-chain Data 5. Comprehensive Security Assessments from Multiple Perspectives 6. Notifications Regarding Blockchain Sentiment The service also supports User Interface and API methods to enhance user interaction and integration.

Access on-chain data more efficiently and at reduced costs, leveraging the trustless capabilities of ZK technology. Utilize transactions, receipts, and historical states directly within your smart contract. Axiom enables computation across the full history of Ethereum, with all operations verified on-chain through ZK proofs. Merge information from block headers, accounts, contract storage, transactions, and receipts seamlessly. Utilize the Axiom SDK to define computations across Ethereum's history using Typescript. Tap into our extensive library of ZK primitives designed for arithmetic, logic, and array functions, all of which can be verified on-chain. Axiom ensures that query outcomes are verified on-chain using ZK proofs before relaying them to your smart contract's callback. Create genuinely trustless on-chain applications with ZK-verified outcomes provided by Axiom. Evaluate and compensate protocol participants completely trustlessly, without relying on external oracles. Recognize and reward contributions to the protocol based on on-chain activity, extending even to external protocols, while also implementing penalties for misconduct according to tailored criteria. This framework fosters a more reliable and accountable decentralized ecosystem.

The integration of TCP/IP and HTTP protocols within blockchain technology can enhance and expand the Internet of Blockchains, facilitating seamless data and application services across both on-chain and off-chain environments. The efficient Inter-Blockchain Communication (IBC) protocol is designed to boost heterogeneous interchain capabilities, allowing for the transfer of NFTs, interaction with smart contracts, and other cross-chain functionalities. This digitization of assets on various blockchains ensures a reliable and efficient means of transferring and distributing value. The cross-chain Automated Market Maker (AMM) protocol emerges as an innovative platform designed specifically for the Cosmos application ecosystem. Within this framework, the IRIS network operates as a vital component of the broader Cosmos network, enabling all zones to communicate with one another via the standardized IBC protocol. By adding a layer of service semantics to the network, we are set to deliver groundbreaking solutions that will open up a myriad of new business opportunities, thereby enhancing both the scale and diversity of the Cosmos ecosystem. Such advancements are poised to significantly transform interactions between different blockchain zones, fostering an interconnected digital landscape.

XDAO – expanding multichain DAO ecosystem built for a decentralized future. The main idea of XDAO is to allow people to create a decentralized autonomous organization of any size. XDAO is working on delivering a product that reveals the full potential of a company on a blockchain by providing it with all the tools they need for successful operations. For more savvy users XDAO can also be described as an off-chain voting mechanism with on‐chain execution. The XDAO is a winner of the BSC Hackathon, HECO Hackathon and also granted by Polygon over the summer of 2021. What makes XDAO different from other DAO builders: – Modular Structure (everything you want to have in your DAO can be implemented through modules: Snapshot Integration, Timelock controller, voice delegation, etc.). – Hybrid voting (Cheaper and faster voting). – Direct Interaction with DeFi through Wallet Connect. – DAO ecosystem where investors can come in, analyze, and invest in the most perspective projects. Who can use XDAO: – Venture Capital Funds. – Asset Management Company. – Public funds and foundations. – Startups. – DeFi projects. – Freelance groups. – NFT owners. – GameFi Guilds.

Hologres is a hybrid serving and analytical processing system designed for the cloud that integrates effortlessly with the big data ecosystem. It enables users to analyze and manage petabyte-scale data with remarkable concurrency and minimal latency. With Hologres, you can leverage your business intelligence tools to conduct multidimensional data analysis and gain insights into your business operations in real-time. This platform addresses common issues faced by traditional real-time data warehousing solutions, such as data silos and redundancy. Hologres effectively fulfills the needs for data migration while facilitating the real-time analysis of extensive data volumes. It delivers responses to queries on petabyte-scale datasets in under a second, empowering users to explore their data dynamically. Additionally, it supports highly concurrent writes and queries, reaching speeds of up to 100 million transactions per second (TPS), ensuring that data is immediately available for querying after it’s written. This immediate access to data enhances the overall efficiency of business analytics.

SelectDB is an innovative data warehouse built on Apache Doris, designed for swift query analysis on extensive real-time datasets. Transitioning from Clickhouse to Apache Doris facilitates the separation of the data lake and promotes an upgrade to a more efficient lake warehouse structure. This high-speed OLAP system handles nearly a billion query requests daily, catering to various data service needs across multiple scenarios. To address issues such as storage redundancy, resource contention, and the complexities of data governance and querying, the original lake warehouse architecture was restructured with Apache Doris. By leveraging Doris's capabilities for materialized view rewriting and automated services, it achieves both high-performance data querying and adaptable data governance strategies. The system allows for real-time data writing within seconds and enables the synchronization of streaming data from databases. With a storage engine that supports immediate updates and enhancements, it also facilitates real-time pre-polymerization of data for improved processing efficiency. This integration marks a significant advancement in the management and utilization of large-scale real-time data.

Apache Kylin™ is a distributed, open-source Analytical Data Warehouse designed for Big Data, aimed at delivering OLAP (Online Analytical Processing) capabilities in the modern big data landscape. By enhancing multi-dimensional cube technology and precalculation methods on platforms like Hadoop and Spark, Kylin maintains a consistent query performance, even as data volumes continue to expand. This innovation reduces query response times from several minutes to just milliseconds, effectively reintroducing online analytics into the realm of big data. Capable of processing over 10 billion rows in under a second, Kylin eliminates the delays previously associated with report generation, facilitating timely decision-making. It seamlessly integrates data stored on Hadoop with popular BI tools such as Tableau, PowerBI/Excel, MSTR, QlikSense, Hue, and SuperSet, significantly accelerating business intelligence operations on Hadoop. As a robust Analytical Data Warehouse, Kylin supports ANSI SQL queries on Hadoop/Spark and encompasses a wide array of ANSI SQL functions. Moreover, Kylin’s architecture allows it to handle thousands of simultaneous interactive queries with minimal resource usage, ensuring efficient analytics even under heavy loads. This efficiency positions Kylin as an essential tool for organizations seeking to leverage their data for strategic insights.

The Ocient Hyperscale Data Warehouse revolutionizes data transformation and loading within seconds, allowing organizations to efficiently store and analyze larger datasets while executing queries on hyperscale data up to 50 times faster. In order to provide cutting-edge data analytics, Ocient has entirely rethought its data warehouse architecture, facilitating rapid and ongoing analysis of intricate, hyperscale datasets. By positioning storage close to compute resources to enhance performance on standard industry hardware, the Ocient Hyperscale Data Warehouse allows users to transform, stream, or load data directly, delivering results for previously unattainable queries in mere seconds. With its optimization for standard hardware, Ocient boasts query performance benchmarks that surpass competitors by as much as 50 times. This innovative data warehouse not only meets but exceeds the demands of next-generation analytics in critical areas where traditional solutions struggle, thereby empowering organizations to achieve greater insights from their data. Ultimately, the Ocient Hyperscale Data Warehouse stands out as a powerful tool in the evolving landscape of data analytics.

BigLake serves as a storage engine that merges the functionalities of data warehouses and lakes, allowing BigQuery and open-source frameworks like Spark to efficiently access data while enforcing detailed access controls. It enhances query performance across various multi-cloud storage systems and supports open formats, including Apache Iceberg. Users can maintain a single version of data, ensuring consistent features across both data warehouses and lakes. With its capacity for fine-grained access management and comprehensive governance over distributed data, BigLake seamlessly integrates with open-source analytics tools and embraces open data formats. This solution empowers users to conduct analytics on distributed data, regardless of its storage location or method, while selecting the most suitable analytics tools, whether they be open-source or cloud-native, all based on a singular data copy. Additionally, it offers fine-grained access control for open-source engines such as Apache Spark, Presto, and Trino, along with formats like Parquet. As a result, users can execute high-performing queries on data lakes driven by BigQuery. Furthermore, BigLake collaborates with Dataplex, facilitating scalable management and logical organization of data assets. This integration not only enhances operational efficiency but also simplifies the complexities of data governance in large-scale environments.

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.

Sequel provides business intelligence solutions tailored for Power Systems™ that operate on IBM i. With robust capabilities for querying and reporting, Sequel simplifies the process of accessing, analyzing, and distributing data in the way that best suits your needs. Offering cost-effective IBM i business intelligence, Sequel caters to IT professionals, business users, and executives alike. Currently, thousands of clients around the globe rely on Sequel to obtain the necessary data precisely when they require it. IT personnel can swiftly deploy the software, seamlessly integrate pre-existing queries from Query/400, and deliver data to end users at remarkable speeds. Furthermore, Sequel’s user-friendly interfaces—including the traditional green screen, the graphical user interface known as Sequel Viewpoint, and web-based options—enable IT to empower business users and executives with direct data access, allowing them to efficiently address more pressing requests. The landscape of iSeries reporting has truly become more manageable and accessible. This enhancement not only streamlines operations but also fosters a data-driven culture within organizations.

Y42 is the first fully managed Modern DataOps Cloud for production-ready data pipelines on top of Google BigQuery and Snowflake.

Qlik Compose for Data Warehouses offers a contemporary solution that streamlines and enhances the process of establishing and managing data warehouses. This tool not only automates the design of the warehouse but also generates ETL code and implements updates swiftly, all while adhering to established best practices and reliable design frameworks. By utilizing Qlik Compose for Data Warehouses, organizations can significantly cut down on the time, expense, and risk associated with BI initiatives, regardless of whether they are deployed on-premises or in the cloud. On the other hand, Qlik Compose for Data Lakes simplifies the creation of analytics-ready datasets by automating data pipeline processes. By handling data ingestion, schema setup, and ongoing updates, companies can achieve a quicker return on investment from their data lake resources, further enhancing their data strategy. Ultimately, these tools empower organizations to maximize their data potential efficiently.

Effortlessly create, edit, and manage your data models without the hassle of needing another tool by using Weld. This platform is equipped with an array of features designed to streamline your data modeling process, including intelligent autocomplete, code folding, error highlighting, audit logs, version control, and collaboration capabilities. Moreover, it utilizes the same text editor as VS Code, ensuring a fast, efficient, and visually appealing experience. Your queries are neatly organized in a library that is not only easily searchable but also accessible at any time. The audit logs provide transparency by showing when a query was last modified and by whom. Weld Model allows you to materialize your models in various formats such as tables, incremental tables, views, or tailored materializations that suit your specific design. Furthermore, you can conduct all your data operations within a single, user-friendly platform, supported by a dedicated team of data analysts ready to assist you. This integrated approach simplifies the complexities of data management, making it more efficient and less time-consuming.

Oracle Autonomous Data Warehouse is a cloud-based data warehousing solution designed to remove the intricate challenges associated with managing a data warehouse, including cloud operations, data security, and the creation of data-centric applications. This service automates essential processes such as provisioning, configuration, security measures, tuning, scaling, and data backup, streamlining the overall experience. Additionally, it features self-service tools for data loading, transformation, and business modeling, along with automatic insights and integrated converged database functionalities that simplify queries across diverse data formats and facilitate machine learning analyses. Available through both the Oracle public cloud and the Oracle Cloud@Customer within client data centers, it offers flexibility to organizations. Industry analysis by experts from DSC highlights the advantages of Oracle Autonomous Data Warehouse, suggesting it is the preferred choice for numerous global enterprises. Furthermore, there are various applications and tools that work seamlessly with the Autonomous Data Warehouse, enhancing its usability and effectiveness.

Hudi serves as a robust platform for constructing streaming data lakes equipped with incremental data pipelines, all while utilizing a self-managing database layer that is finely tuned for lake engines and conventional batch processing. It effectively keeps a timeline of every action taken on the table at various moments, enabling immediate views of the data while also facilitating the efficient retrieval of records in the order they were received. Each Hudi instant is composed of several essential components, allowing for streamlined operations. The platform excels in performing efficient upserts by consistently linking a specific hoodie key to a corresponding file ID through an indexing system. This relationship between record key and file group or file ID remains constant once the initial version of a record is written to a file, ensuring stability in data management. Consequently, the designated file group encompasses all iterations of a collection of records, allowing for seamless data versioning and retrieval. This design enhances both the reliability and efficiency of data operations within the Hudi ecosystem.

bi(OS)® offers an unmatched speed to insight for developers of data applications in a cohesive manner. With bi(OS)®, the entire process of creating data applications can be completed in just a matter of hours to days. This comprehensive approach encompasses the integration of diverse data sources, the extraction of real-time insights, and the smooth deployment into production environments. By joining forces with enterprise data teams across various sectors, you can transform into the data superhero your organization needs. The combination of Open Source, Cloud, and SaaS has not fulfilled its potential for delivering genuine data-driven results. Enterprises have largely focused their investments on data movement and integration, a strategy that is ultimately unsustainable. A fresh perspective on data management is urgently required, one that considers the unique challenges of enterprises. bi(OS)® is designed by rethinking fundamental principles in enterprise data management, ranging from data ingestion to insight generation. It caters to the needs of API, AI, and BI developers in a cohesive manner, enabling data-driven outcomes within days. As engineers collaborate effectively, a harmonious relationship emerges among IT teams, tools, and processes, creating a lasting competitive advantage for the organization.

Many Contract Research Organizations (CROs), as well as drug developers, who conduct toxicology studies internally or externally, find it challenging and critical to consolidate and validate data sets. Savante allows your organization to create, merge and validate preclinical study data from any source. Savante allows scientists and managers to view preclinical data in SEND format. The Savante repository automatically syncs preclinical data from Pristima XD. Data from other sources can also be merged through import and migration, as well as direct loads of data sets. The Savante toolkit handles all the necessary consolidation, study merging and control terminology mapping.

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.

Agile Data Engine serves as a robust DataOps platform crafted to optimize the lifecycle of cloud-based data warehouses, encompassing their development, deployment, and management. This solution consolidates data modeling, transformation processes, continuous deployment, workflow orchestration, monitoring, and API integration into a unified SaaS offering. By leveraging a metadata-driven model, it automates the generation of SQL scripts and the workflows for data loading, significantly boosting efficiency and responsiveness in data operations. The platform accommodates a variety of cloud database systems such as Snowflake, Databricks SQL, Amazon Redshift, Microsoft Fabric (Warehouse), Azure Synapse SQL, Azure SQL Database, and Google BigQuery, thus providing considerable flexibility across different cloud infrastructures. Furthermore, its modular data product architecture and pre-built CI/CD pipelines ensure smooth integration and facilitate ongoing delivery, empowering data teams to quickly adjust to evolving business demands. Additionally, Agile Data Engine offers valuable insights and performance metrics related to the data platform, enhancing overall operational transparency and effectiveness. This capability allows organizations to make informed decisions based on real-time data analytics, further driving strategic initiatives.