Alternatives to Onehouse

Accelerate your data journey with AnalyticsCreator. Automate the design, development, and deployment of modern data architectures, including dimensional models, data marts, and data vaults or a combination of modeling techniques. Seamlessly integrate with leading platforms like Microsoft Fabric, Power BI, Snowflake, Tableau, and Azure Synapse and more. Experience streamlined development with automated documentation, lineage tracking, and schema evolution. Our intelligent metadata engine empowers rapid prototyping and deployment of analytics and data solutions. Reduce time-consuming manual tasks, allowing you to focus on data-driven insights and business outcomes. AnalyticsCreator supports agile methodologies and modern data engineering workflows, including CI/CD. Let AnalyticsCreator handle the complexities of data modeling and transformation, enabling you to unlock the full potential of your data

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

Data lakehouse is an open architecture that allows you to store, understand and analyze all of your data. It combines the power, richness, and flexibility of data warehouses with the breadth of open-source data technologies. A data lakehouse can easily be built on Oracle Cloud Infrastructure (OCI). It can also be used with pre-built AI services such as Oracle's language service and the latest AI frameworks. Data Flow, a serverless Spark service, allows our customers to concentrate on their Spark workloads using zero infrastructure concepts. Customers of Oracle want to build machine learning-based analytics on their Oracle SaaS data or any SaaS data. Our easy-to-use connectors for Oracle SaaS make it easy to create a lakehouse to analyze all of your SaaS data and reduce time to solve problems.

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.

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

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

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.

Qlik Data Integration platform automates the process for providing reliable, accurate and trusted data sets for business analysis. Data engineers are able to quickly add new sources to ensure success at all stages of the data lake pipeline, from real-time data intake, refinement, provisioning and governance. This is a simple and universal solution to continuously ingest enterprise data into popular data lake in real-time. This model-driven approach allows you to quickly design, build, and manage data lakes in the cloud or on-premises. To securely share all your derived data sets, create a smart enterprise-scale database catalog.

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

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

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

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.

Hydrolix is a streaming lake of data that combines decoupled archiving, indexed searching, and stream processing for real-time query performance on terabyte scale at a dramatically lower cost. CFOs love that data retention costs are 4x lower. Product teams appreciate having 4x more data at their disposal. Scale up resources when needed and down when not. Control costs by fine-tuning resource consumption and performance based on workload. Imagine what you could build if you didn't have budget constraints. Log data from Kafka, Kinesis and HTTP can be ingested, enhanced and transformed. No matter how large your data, you will only get the data that you need. Reduce latency, costs, and eliminate timeouts and brute-force queries. Storage is decoupled with ingest and queries, allowing them to scale independently to meet performance and cost targets. Hydrolix's HDX (high-density compress) reduces 1TB to 55GB.

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

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

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.

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

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

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

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

Hudi is a rich platform for building streaming data lakes using incremental data pipelines on a self managing database layer. It can also be optimized for regular batch processing and lake engines. Hudi keeps a timeline of all actions on the table at different times. This allows for instantaneous views and efficient retrieval of data in the order they were received. The following components make up a Hudi instant. Hudi provides efficient upserts by mapping a given Hoodie key consistently with a file ID, via an indexing mechanism. Once a record is written to a file, the mapping between record key/file group/file ID never changes. The mapped file group includes all versions of a group record.

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

Lentiq is a data lake that allows small teams to do big tasks. You can quickly run machine learning, data science, and data analysis at scale in any cloud. Lentiq allows your teams to ingest data instantly and then clean, process, and share it. Lentiq allows you to create, train, and share models within your organization. Lentiq allows data teams to collaborate and invent with no restrictions. Data lakes are storage and process environments that provide ML, ETL and schema-on-read querying capabilities. Are you working on data science magic? A data lake is a must. The big, centralized data lake of the Post-Hadoop era is gone. Lentiq uses data pools, which are interconnected, multi-cloud mini-data lakes. They all work together to provide a stable, secure, and fast data science environment.

Azure Data Lake offers all the capabilities needed to make it easy to store and analyze data across all platforms and languages. It eliminates the complexity of ingesting, storing, and streaming data, making it easier to get up-and-running with interactive, batch, and streaming analytics. Azure Data Lake integrates with existing IT investments to simplify data management and governance. It can also seamlessly integrate with existing IT investments such as data warehouses and operational stores, allowing you to extend your current data applications. We have the experience of working with enterprise customers, running large-scale processing and analytics for Microsoft businesses such as Office 365, Microsoft Windows, Bing, Azure, Windows, Windows, and Microsoft Windows. Azure Data Lake solves many productivity and scaling issues that prevent you from maximizing the potential of your data.

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.

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

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

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

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

NewEvol is a technologically advanced product suite that uses advanced analytics and data science to identify anomalies in data. NewEvol is a powerful tool that can be used to compile data for small and large enterprises. It supports rule-based alerting, visualization, automation, and responses. NewEvol is a robust system that can handle challenging business requirements. NewEvol Expertise 1. Data Lake 2. SIEM 3. SOAR 4. Threat Intelligence 5. Analytics

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

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).

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.

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

Varada's adaptive and dynamic big data indexing solution allows you to balance cost and performance with zero data-ops. Varada's big data indexing technology is a smart acceleration layer for your data lake. It remains the single source and truth and runs in the customer's cloud environment (VPC). Varada allows data teams to democratize data. It allows them to operationalize the entire data lake and ensures interactive performance without the need for data to be moved, modelled, or manually optimized. Our ability to dynamically and automatically index relevant data at the source structure and granularity is our secret sauce. Varada allows any query to meet constantly changing performance and concurrency requirements of users and analytics API calls. It also keeps costs predictable and under control. The platform automatically determines which queries to speed up and which data to index. Varada adjusts the cluster elastically to meet demand and optimize performance and cost.

Agile Data Engine is an integrated DataOps platform that streamlines the development, deployment and operation of cloud data warehouses. It integrates data modelling, transformations and continuous deployment with workflow orchestration, API connectivity, monitoring and API connectivity in a single SaaS. The platform's metadata driven approach automates SQL generation and data loading workflows, increasing productivity and agility in data operation. Agile Data Engine supports multiple cloud database platforms including Snowflake SQL, Databricks SQL and Amazon Redshift. It also supports Azure Synapse SQL (Warehouse), Azure SQL Database and Google BigQuery. Agile Data Engine's modular data product architecture and pre-built CI/CD pipelines enable seamless integration and continuous deployment, allowing data teams to quickly adapt to changing business needs. The platform provides statistics and insights on the performance of data platforms.

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.

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

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

Dataleyk is a secure, fully-managed cloud platform for SMBs. Our mission is to make Big Data analytics accessible and easy for everyone. Dataleyk is the missing piece to achieving your data-driven goals. Our platform makes it easy to create a stable, flexible, and reliable cloud data lake without any technical knowledge. All of your company data can be brought together, explored with SQL, and visualized with your favorite BI tool. Dataleyk will modernize your data warehouse. Our cloud-based data platform is capable of handling both structured and unstructured data. Data is an asset. Dataleyk, a cloud-based data platform, encrypts all data and offers data warehousing on-demand. Zero maintenance may not be an easy goal. It can be a catalyst for significant delivery improvements, and transformative results.

Peliqan.io provides a data platform that is all-in-one for business teams, IT service providers, startups and scale-ups. No data engineer required. Connect to databases, data warehouses, and SaaS applications. In a spreadsheet interface, you can explore and combine data. Business users can combine multiple data sources, clean data, edit personal copies, and apply transformations. Power users can use SQL on anything, and developers can use Low-code to create interactive data apps, implement writing backs and apply machine intelligence.