Bobsled Alternatives

BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more data-driven.

Qrvey is the only solution for embedded analytics with a built-in data lake. Qrvey saves engineering teams time and money with a turnkey solution connecting your data warehouse to your SaaS application. Qrvey’s full-stack solution includes the necessary components so that your engineering team can build less. Qrvey’s multi-tenant data lake includes: - Elasticsearch as the analytics engine - A unified data pipeline for ingestion and transformation - A complete semantic layer for simple user and data security integration Qrvey’s embedded visualizations support everything from: - standard dashboards and templates - self-service reporting - user-level personalization - individual dataset creation - data-driven workflow automation Qrvey delivers this as a self-hosted package for cloud environments. This offers the best security as your data never leaves your environment while offering a better analytics experience to users. Less time and money on analytics

The best insights are based on the most complete, most accurate, and most timely data. Minitab Connect empowers data users from across the enterprise with self-serve tools to transform diverse data into a governed network of data pipelines, feed analytics initiatives and foster organization-wide collaboration. Users can effortlessly blend and explore data from databases, cloud and on-premise apps, unstructured data, spreadsheets, and more. Flexible, automated workflows accelerate every step of the data integration process, while powerful data preparation and visualization tools help yield transformative insights. Flexible, intuitive data integration tools let users connect and blend data from a variety of internal and external sources, like data warehouses, data lakes, IoT devices, SaaS applications, cloud storage, spreadsheets, and email.

More customers pick Amazon Redshift than any other cloud data warehouse. Redshift powers analytical workloads for Fortune 500 companies, startups, and everything in between. Companies like Lyft have grown with Redshift from startups to multi-billion dollar enterprises. No other data warehouse makes it as easy to gain new insights from all your data. With Redshift you can query petabytes of structured and semi-structured data across your data warehouse, operational database, and your data lake using standard SQL. Redshift lets you easily save the results of your queries back to your S3 data lake using open formats like Apache Parquet to further analyze from other analytics services like Amazon EMR, Amazon Athena, and Amazon SageMaker. Redshift is the world’s fastest cloud data warehouse and gets faster every year. For performance intensive workloads you can use the new RA3 instances to get up to 3x the performance of any cloud data warehouse.

If you're familiar with cloud storage, you'll find buckets easy to understand. However, unlike traditional cloud services, buckets are built on open, decentralized protocols including the IPFS and Libp2p. You can serve websites, data, and apps from buckets. Explore your Buckets on the Hub gateway. Render web content in your Bucket on a persistent website. Automatically distribute your updates on IPFS using IPNS. Collaboratively manage Buckets as an organization. Create private Buckets where your app users can store data. Archive Bucket data on Filecoin to ensure long-term security and access to your files. To start a Bucket in your current working directory, you must first initialize it. You can initialize a bucket with an existing UnixFS DAG, available in the IPFS network, or import it interactively in an existing bucket. You can create buckets to share with all members of an organization.

Whether you want to build a governed delta lake, data warehouse, or simply want to migrate from your traditional database to a modern cloud data warehouse, do it all with Lyftrondata. Simply create and manage all of your data workloads on one platform by automatically building your pipeline and warehouse. Analyze it instantly with ANSI SQL, BI/ML tools, and share it without worrying about writing any custom code. Boost the productivity of your data professionals and shorten your time to value. Define, categorize, and find all data sets in one place. Share these data sets with other experts with zero codings and drive data-driven insights. This data sharing ability is perfect for companies that want to store their data once, share it with other experts, and use it multiple times, now and in the future. Define dataset, apply SQL transformations or simply migrate your SQL data processing logic to any cloud data warehouse.

BigLake is a storage engine that unifies data warehouses and lakes by enabling BigQuery and open-source frameworks like Spark to access data with fine-grained access control. BigLake provides accelerated query performance across multi-cloud storage and open formats such as Apache Iceberg. Store a single copy of data with uniform features across data warehouses & lakes. Fine-grained access control and multi-cloud governance over distributed data. Seamless integration with open-source analytics tools and open data formats. Unlock analytics on distributed data regardless of where and how it’s stored, while choosing the best analytics tools, open source or cloud-native over a single copy of data. Fine-grained access control across open source engines like Apache Spark, Presto, and Trino, and open formats such as Parquet. Performant queries over data lakes powered by BigQuery. Integrates with Dataplex to provide management at scale, including logical data organization.

Bitfount is a platform for distributed data science. We power deep data collaborations without data sharing. Distributed data science sends algorithms to data, instead of the other way around. Set up a federated privacy-preserving analytics and machine learning network in minutes, and let your team focus on insights and innovation instead of bureaucracy. Your data team has the skills to solve your biggest challenges and innovate, but they are held back by barriers to data access. Is complex data pipeline infrastructure messing with your plans? Are compliance processes taking too long? Bitfount has a better way to unleash your data experts. Connect siloed and multi-cloud datasets while preserving privacy and respecting commercial sensitivity. No expensive, time-consuming data lift-and-shift. Usage-based access controls to ensure teams only perform the analysis you want, on the data you want. Transfer management of access controls to the teams who control the data.

Dremio delivers lightning-fast queries and a self-service semantic layer directly on your data lake storage. No moving data to proprietary data warehouses, no cubes, no aggregation tables or extracts. Just flexibility and control for data architects, and self-service for data consumers. Dremio technologies like Data Reflections, Columnar Cloud Cache (C3) and Predictive Pipelining work alongside Apache Arrow to make queries on your data lake storage very, very fast. An abstraction layer enables IT to apply security and business meaning, while enabling analysts and data scientists to explore data and derive new virtual datasets. Dremio’s semantic layer is an integrated, searchable catalog that indexes all of your metadata, so business users can easily make sense of your data. Virtual datasets and spaces make up the semantic layer, and are all indexed and searchable.

The only fully managed cloud data lakehouse designed to ingest from all your data sources in minutes and support all your query engines at scale, for a fraction of the cost. Ingest from databases and event streams at TB-scale in near real-time, with the simplicity of fully managed pipelines. Query your data with any engine, and support all your use cases including BI, real-time analytics, and AI/ML. Cut your costs by 50% or more compared to cloud data warehouses and ETL tools with simple usage-based pricing. Deploy in minutes without engineering overhead with a fully managed, highly optimized cloud service. Unify your data in a single source of truth and eliminate the need to copy data across data warehouses and lakes. Use the right table format for the job, with omnidirectional interoperability between Apache Hudi, Apache Iceberg, and Delta Lake. Quickly configure managed pipelines for database CDC and streaming ingestion.

Automatically ingest marketing data into any data warehouse or cloud file storage of your choice such as BigQuery, Snowflake, Redshift, Azure SQL, AWS S3, Azure Data Lake, Google Cloud Storage with our fully managed ETL pipelines in the cloud. Our hosted marketing data warehouse integrates all your marketing data and provides ad insights, cross-channel attribution, content insights, competitor Insights, and more. Our customer data platform performs identity resolution in real-time across data sources thus enabling a unified view of the customer and their journey. Electrik.AI is a cloud-based marketing analytics software and full-service platform. Electrik.AI’s Google Analytics Hit Data Extractor enriches and extracts the un-sampled hit level data sent to Google Analytics from the website or application and periodically ships it to your desired destination database/data warehouse or file/data lake.

Data integration, backup, management, and connectivity. 100 % cloud based platform that offers contemporary cloud agility and scalability, eliminating the need of deployment or manual upgrades. No coding wizard-based solution that meets the needs of both IT professionals and business users with no technical skills. With flexible pricing plans for each product, Skyvia suites for businesses of any size, from a small startup to an enterprise company. Connect your cloud, on-premise, and flat data to automate workflows. Automate data collection from disparate cloud sources to a database or data warehouse. Transfer your business data between cloud apps automatically in just a few clicks. Protect all your cloud data and keep it secure in one place. Share data in real time via REST API to connect with multiple OData consumers. Query and manage any data from the browser via SQL or intuitive visual Query Builder.

Store, archive, manage, and collaborate on multi-omic datasets. Illumina Connected Analytics is a secure genomic data platform to operationalize informatics and drive scientific insights. Easily import, build, and edit workflows with tools like CWL and Nextflow. Leverage DRAGEN bioinformatics pipelines. Organize data in a secure workspace and share it globally in a compliant manner. Keep your data in your cloud environment while using our platform. Visualize and interpret your data with a flexible analysis environment, including JupyterLab Notebooks. Aggregate, query, and analyze sample and population data in a scalable data warehouse. Scale analysis operations by building, validating, automating, and deploying informatics pipelines. Reduce the time required to analyze genomic data, when swift results can be a critical factor. Enable comprehensive profiling to identify novel drug targets and drug response biomarkers. Flow data seamlessly from Illumina sequencing systems.

The Qlik Data Integration platform for managed data lakes automates the process of providing continuously updated, accurate, and trusted data sets for business analytics. Data engineers have the agility to quickly add new sources and ensure success at every step of the data lake pipeline from real-time data ingestion, to refinement, provisioning, and governance. A simple and universal solution for continually ingesting enterprise data into popular data lakes in real-time. A model-driven approach for quickly designing, building, and managing data lakes on-premises or in the cloud. Deliver a smart enterprise-scale data catalog to securely share all of your derived data sets with business users.

Promethium helps data and analytics teams work smarter so they can stay ahead of growing data volumes and business needs. Simply connecting to a data warehouse or data lake to get access to raw data is not enough. Datasets require a lot of hard work from data teams! Data Teams aren't growing as fast as data volumes or business demand for data. Promethium helps overloaded data teams work smarter so they can deliver faster. Rely less on ETL, with access data on demand where it lives. Moving less data saves time and money. With Promethium one person can do in minutes what typically takes a team months using 6 or more tools. With a few clicks and without writing code, connect and catalog data sources and create and query cross-source datasets. Less custom code and ETL. Validate data is correct in real-time, not after months of work and ETL. Instantly share work so that it is reused, instead of recreated.

Amazon Macie is a fully managed data security and data privacy service that uses machine learning and pattern matching to discover and protect your sensitive data in AWS. As organizations manage growing volumes of data, identifying and protecting their sensitive data at scale can become increasingly complex, expensive, and time-consuming. Amazon Macie automates the discovery of sensitive data at scale and lowers the cost of protecting your data. Macie automatically provides an inventory of Amazon S3 buckets including a list of unencrypted buckets, publicly accessible buckets, and buckets shared with AWS accounts outside those you have defined in AWS Organizations. Then, Macie applies machine learning and pattern matching techniques to the buckets you select to identify and alert you to sensitive data, such as personally identifiable information (PII).

Dataddo is a fully-managed, no-code data integration platform that connects cloud-based applications and dashboarding tools, data warehouses, and data lakes. It offers 3 main products: - Data to Dashboards: Send data from apps to dashboarding tools for insights in record time. A free version is available for this product! - Data Anywhere: Send data from apps to warehouses and dashboards, between warehouses, and from warehouses into apps. - Headless Data Integration: Build your own data product on top of the unified Dataddo API. The company’s engineers manage all API changes, proactively monitor and fix pipelines, and build new connectors free of charge in around 10 business days. From first login to complete, automated pipelines, get your data flowing from sources to destinations in just a few clicks.

Powered by Apache Doris, VeloDB is a modern data warehouse for lightning-fast analytics on real-time data at scale. Push-based micro-batch and pull-based streaming data ingestion within seconds. Storage engine with real-time upsert、append and pre-aggregation. Unparalleled performance in both real-time data serving and interactive ad-hoc queries. Not just structured but also semi-structured data. Not just real-time analytics but also batch processing. Not just run queries against internal data but also work as a federate query engine to access external data lakes and databases. Distributed design to support linear scalability. Whether on-premise deployment or cloud service, separation or integration of storage and compute, resource usage can be flexibly and efficiently adjusted according to workload requirements. Built on and fully compatible with open source Apache Doris. Support MySQL protocol, functions, and SQL for easy integration with other data tools.

Cumulative storage accounts for usage variance across users and optimizes the storage provisioning saving enormously. Open for Integration - Open standards-based integration with a wide range of collaboration tools, client applications, and business applications. Integrate with third-party ESGs, DLPs, mail notifiers, and several other tools to define your stack. Co-exist with external cloud workspace solutions to develop cost-optimal multi-cloud hybrids. Back up your critical email data, manage your ever-growing mailbox storage with cloud-native data protection. Share files, organize ideas and initiatives with note-based team collaboration. Add-on Vaultastic to back up your critical email data and benefit from the on-demand discovery, improved compliance postures and reduced data loss/tampering risks. Cumulative storage, choice of free and paid clients, zero management, maintenance all add up to reducing costs substantially.

Data is being reconstructed for the cloud. Identity has taken a new definition beyond just humans, extending to service accounts and principals. Authorization is the truest form of identity. The multi-cloud world requires a novel, dynamic approach to secure enterprise data. Only Veza can give you a comprehensive view of authorization across your identity-to-data relationships. Veza is a cloud-native, agentless platform, and introduces no risk to your data or its availability. We make it easy for you to manage authorization across your entire cloud ecosystem so you can empower your users to share data securely. Veza supports the most common critical systems from day one — unstructured data systems, structured data systems, data lakes, cloud IAM, and apps — and makes it possible for you to bring your own custom apps by leveraging Veza’s Open Authorization API.

PuppyGraph empowers you to seamlessly query one or multiple data stores as a unified graph model. Graph databases are expensive, take months to set up, and need a dedicated team. Traditional graph databases can take hours to run multi-hop queries and struggle beyond 100GB of data. A separate graph database complicates your architecture with brittle ETLs and inflates your total cost of ownership (TCO). Connect to any data source anywhere. Cross-cloud and cross-region graph analytics. No complex ETLs or data replication is required. PuppyGraph enables you to query your data as a graph by directly connecting to your data warehouses and lakes. This eliminates the need to build and maintain time-consuming ETL pipelines needed with a traditional graph database setup. No more waiting for data and failed ETL processes. PuppyGraph eradicates graph scalability issues by separating computation and storage.

AI teams face challenges that require new technologies. We build these technologies. Existing data warehouses and data lakes do not fit unstructured datasets like text, images, and videos. AI hand in hand with software development. Built with data scientists, ML engineers, and data engineers in mind. Don’t reinvent the wheel! Fast and cost‑efficient path to production. Your data is always stored by you. Your models are trained on your machines. Existing data warehouses and data lakes do not fit unstructured datasets like text, images, and videos. AI teams face challenges that require new technologies. We build these technologies. Studio is an extension of GitHub, GitLab or BitBucket. Sign up for the online SaaS version or contact us to get on-premise installation

Automatically indexed warehouses, lakes, dashboards, and other pieces of your data stack. Combined with utilization, lineage, and other social popularity signals, Metaphor lets you show the most trusted data to your users. Provide an open 360 view of your data and conversations about data to everyone in the organization. Meet your customers where they are - share artifacts from the catalog including documentation, natively via Slack. Tag insightful Slack conversations and associate them with data. Collaborate across silos by the organic discovery of important terms and usage patterns. Easily discover data across the entire stack, write technical details and Business friendly wiki that is easily consumed by non-technical users. Support your users directly in Slack and use the catalog as a Data Enablement tool to quickly onboard users for a more personalized experience.

Etleap was built from the ground up on AWS to support Redshift and snowflake data warehouses and S3/Glue data lakes. Their solution simplifies and automates ETL by offering fully-managed ETL-as-a-service. Etleap's data wrangler and modeling tools let users control how data is transformed for analysis, without writing any code. Etleap monitors and maintains data pipelines for availability and completeness, eliminating the need for constant maintenance, and centralizes data from 50+ disparate sources and silos into your data warehouse or data lake.

Open core, delivering hybrid and multi-cloud integration. Data Fusion is built using open source project CDAP, and this open core ensures data pipeline portability for users. CDAP’s broad integration with on-premises and public cloud platforms gives Cloud Data Fusion users the ability to break down silos and deliver insights that were previously inaccessible. Integrated with Google’s industry-leading big data tools. Data Fusion’s integration with Google Cloud simplifies data security and ensures data is immediately available for analysis. Whether you’re curating a data lake with Cloud Storage and Dataproc, moving data into BigQuery for data warehousing, or transforming data to land it in a relational store like Cloud Spanner, Cloud Data Fusion’s integration makes development and iteration fast and easy.

lakeFS enables you to manage your data lake the way you manage your code. Run parallel pipelines for experimentation and CI/CD for your data. Simplifying the lives of engineers, data scientists and analysts who are transforming the world with data. lakeFS is an open source platform that delivers resilience and manageability to object-storage based data lakes. With lakeFS you can build repeatable, atomic and versioned data lake operations, from complex ETL jobs to data science and analytics. lakeFS supports AWS S3, Azure Blob Storage and Google Cloud Storage (GCS) as its underlying storage service. It is API compatible with S3 and works seamlessly with all modern data frameworks such as Spark, Hive, AWS Athena, Presto, etc. lakeFS provides a Git-like branching and committing model that scales to exabytes of data by utilizing S3, GCS, or Azure Blob for storage.

Lentiq is a collaborative data lake as a service environment that’s built to enable small teams to do big things. Quickly run data science, machine learning and data analysis at scale in the cloud of your choice. With Lentiq, your teams can ingest data in real time and then process, clean and share it. From there, Lentiq makes it possible to build, train and share models internally. Simply put, data teams can collaborate with Lentiq and innovate with no restrictions. Data lakes are storage and processing environments, which provide ML, ETL, schema-on-read querying capabilities and so much more. Are you working on some data science magic? You definitely need a data lake. In the Post-Hadoop era, the big, centralized data lake is a thing of the past. With Lentiq, we use data pools, which are multi-cloud, interconnected mini-data lakes. They work together to give you a stable, secure and fast data science environment.

QuerySurge leverages AI to automate the data validation and ETL testing of Big Data, Data Warehouses, Business Intelligence Reports and Enterprise Apps/ERPs with full DevOps functionality for continuous testing. Use Cases - Data Warehouse & ETL Testing - Hadoop & NoSQL Testing - DevOps for Data / Continuous Testing - Data Migration Testing - BI Report Testing - Enterprise App/ERP Testing QuerySurge Features - Projects: Multi-project support - AI: automatically create datas validation tests based on data mappings - Smart Query Wizards: Create tests visually, without writing SQL - Data Quality at Speed: Automate the launch, execution, comparison & see results quickly - Test across 200+ platforms: Data Warehouses, Hadoop & NoSQL lakes, databases, flat files, XML, JSON, BI Reports - DevOps for Data & Continuous Testing: RESTful API with 60+ calls & integration with all mainstream solutions - Data Analytics & Data Intelligence:  Analytics dashboard & reports

Build predictive models that never stop improving without complex engineering. Connect to your existing cloud data warehouse and leverage all your data where it already lives. Share features and deploy state-of-the-art ML models with nothing but SQL or dbt or extend with Python. Maintain predictions directly in your data warehouse for easy consumption by your BI and operational tools. Maintain features and predictions directly in your data warehouse without new infrastructure. Build state-of-the-art models that leverage all your data without writing code or pipelines. Unite analytics and AI teams with full extensibility of Continual's declarative AI engine. Govern features, models, and policies with a declarative GitOps workflow as you scale. Accelerate model development with a shared feature store and data-first workflow.

Literally. Supermetrics picks up all the marketing data you need and brings it to your go-to reporting, analytics, or storage platform — whether that’s a BI tool, a spreadsheet, a data visualization tool, a data lake, or a data warehouse. Quickly bring any metrics and dimensions from your favorite marketing platforms into your go-to reporting, data visualization, data warehousing, or BI tool. No sampling. No nonsense. Once you have your data where you want it, you can start organizing and filtering it immediately. Dive into your numbers to figure out what is and isn’t working — and then get straight into optimization. When you’ve built your report or dashboard, you can eliminate hours of manual work by scheduling data transfers and automating your marketing reporting.

Qlik Compose for Data Warehouses (formerly Attunity Compose for Data Warehouses) provides a modern approach by automating and optimizing data warehouse creation and operation. Qlik Compose automates designing the warehouse, generating ETL code, and quickly applying updates, all whilst leveraging best practices and proven design patterns. Qlik Compose for Data Warehouses dramatically reduces the time, cost and risk of BI projects, whether on-premises or in the cloud. Qlik Compose for Data Lakes (formerly Attunity Compose for Data Lakes) automates your data pipelines to create analytics-ready data sets. By automating data ingestion, schema creation, and continual updates, organizations realize faster time-to-value from their existing data lake investments.

Reduce the likelihood of insider threats, data breaches and ransomware attacks. Maximize organizational adherence to regulatory compliance requirements and cyber-security best practices and standards. Sharing large files or massive folders can be a huge pain. AlephTransfer makes it easier and makes external sharing seamless. Aleph Transfer is the fastest and most reliable way to transfer time-critical files. AlephTransfer helps in reducing infrastructure maintenance cost, increasing employee productivity gain, and boosting project efficiency. Today, Business Email Compromise (BEC) is responsible for over 50% of cybercrime losses. At the same time, organizations throughout virtually every industry continue to share highly sensitive information via low-security email attachments or easily breached cloud sharing services. At AlephTransfer, our streamlined Managed File Transfer (MFT) platform was designed to promote a smooth workflow while keeping files safe.

Stitch is a cloud-based platform for ETL – extract, transform, and load. More than a thousand companies use Stitch to move billions of records every day from SaaS applications and databases into data warehouses and data lakes.

Carbonite Information Archiving helps organizations meet changing regulatory requirements by securing and managing critical data. Our solution stores files and communications from email, SMS and social media platforms. Carbonite Information Archiving helps protect your organization against compliance violations and unplanned litigations. Unified archiving of more than 50 data sources – email, Microsoft Teams, IM/collaboration tools and social media. Instantly and securely share a dataset with anyone without compromising security with SimplyShare – no need for an SFTP site or external hard drive. Unlimited cloud-based storage capacity and eDiscovery. Instantly and securely share a dataset with anyone without compromising security with SimplyShare – no need for an SFTP site or external hard drive. Modern interface with intuitive search capabilities.

erwin Data Catalog by Quest is metadata management software that helps organizations learn what data they have and where it’s located, including data at rest and in motion. It tells you the data and metadata available for a certain topic so those particular sources and assets can be found quickly for analysis and decision-making. erwin Data Catalog automates the processes involved in harvesting, integrating, activating and governing enterprise data according to business requirements. This automation results in greater accuracy and faster time to value for data governance and digital transformation efforts, including data warehouse, data lake, data vault and other Big Data deployments, cloud migrations, etc. Metadata management is key to sustainable data governance and any other organizational effort for which data is key to the outcome. erwin Data Catalog automates enterprise metadata management, data mapping, data cataloging, code generation, data profiling and data lineage.

DataLakeHouse.io (DLH.io) Data Sync provides replication and synchronization of operational systems (on-premise and cloud-based SaaS) data into destinations of their choosing, primarily Cloud Data Warehouses. Built for marketing teams and really any data team at any size organization, DLH.io enables business cases for building single source of truth data repositories, such as dimensional data warehouses, data vault 2.0, and other machine learning workloads. Use cases are technical and functional including: ELT, ETL, Data Warehouse, Pipeline, Analytics, AI & Machine Learning, Data, Marketing, Sales, Retail, FinTech, Restaurant, Manufacturing, Public Sector, and more. DataLakeHouse.io is on a mission to orchestrate data for every organization particularly those desiring to become data-driven, or those that are continuing their data driven strategy journey. DataLakeHouse.io (aka DLH.io) enables hundreds of companies to managed their cloud data warehousing and analytics solutions.

Stay focused on delivering valuable and impressive reporting, analytics and insights, instead of being stuck in data warehouse code. Don’t let your data warehouse become a jumble of 100’s of hard-to-maintain pipelines, notebooks, stored procedures, tables. and views etc. Dimodelo DW Studio dramatically reduces the effort required to design, build, deploy and run a data warehouse. Design, generate and deploy a data warehouse targeting Azure Synapse Analytics. Generating a best practice architecture utilizing Azure Data Lake, Polybase and Azure Synapse Analytics, Dimodelo Data Warehouse Studio delivers a high-performance, modern data warehouse in the cloud. Utilizing parallel bulk loads and in-memory tables, Dimodelo Data Warehouse Studio generates a best practice architecture that delivers a high-performance, modern data warehouse in the cloud.

Let Kyligence Zen take care of collecting, organizing, and analyzing your metrics so you can focus more on taking action Kyligence Zen is the go-to low-code metrics platform to define, collect, and analyze your business metrics. It empowers users to quickly connect their data sources, define their business metrics, uncover hidden insights in minutes, and share them across their organization. Kyligence Enterprise provides diverse solutions based on on-premise, public cloud, and private cloud, helping enterprises of any size to simplify multidimensional analysis based on massive amounts of data according to their business needs.​ Kyligence Enterprise, based on Apache Kylin, provides sub-second standard SQL query responses based on PB-scale datasets, simplifying multidimensional data analysis on data lakes for enterprises and enabling business users to quickly discover business value in massive amounts of data and drive better business decisions.

Find out why the heavy hitters are using the Crux external data automation platform to scale external data integration, transformation, and observability without increasing headcount. Our cloud-native data integration technology accelerates the ingestion, preparation, observability and ongoing delivery of any external dataset. The result is that we can ensure you get quality data in the right place, in the right format when you need it. Leverage automatic schema detection, delivery schedule inference, and lifecycle management to build pipelines from any external data source quickly. Enhance discoverability throughout your organization through a private catalog of linked and matched data products. Enrich, validate, and transform any dataset to quickly combine it with other data sources and accelerate analytics.

Generative AI may be new, but we've been building for this day for the past 5 years. Deep Lake thus combines the power of both data lakes and vector databases to build and fine-tune enterprise-grade, LLM-based solutions, and iteratively improve them over time. Vector search does not resolve retrieval. To solve it, you need a serverless query for multi-modal data, including embeddings or metadata. Filter, search, & more from the cloud or your laptop. Visualize and understand your data, as well as the embeddings. Track & compare versions over time to improve your data & your model. Competitive businesses are not built on OpenAI APIs. Fine-tune your LLMs on your data. Efficiently stream data from remote storage to the GPUs as models are trained. Deep Lake datasets are visualized right in your browser or Jupyter Notebook. Instantly retrieve different versions of your data, materialize new datasets via queries on the fly, and stream them to PyTorch or TensorFlow.

The biggest challenge to scaling AI-powered decision-making is unused data. IBM Cloud Pak® for Data is a unified platform that delivers a data fabric to connect and access siloed data on-premises or across multiple clouds without moving it. Simplify access to data by automatically discovering and curating it to deliver actionable knowledge assets to your users, while automating policy enforcement to safeguard use. Further accelerate insights with an integrated modern cloud data warehouse. Universally safeguard data usage with privacy and usage policy enforcement across all data. Use a modern, high-performance cloud data warehouse to achieve faster insights. Empower data scientists, developers and analysts with an integrated experience to build, deploy and manage trustworthy AI models on any cloud. Supercharge analytics with Netezza, a high-performance data warehouse.

Operationalize your data pipelines with privacy-centric data management software. Trūata Calibrate empowers organizations to make data usable while leveraging privacy as a commercial differentiator. Our frictionless, cloud-native software enables businesses to operationalize privacy-compliant data pipelines at speed, so teams can work with data responsibly and confidently. Powered by intelligent automation, Trūata Calibrate facilitates fast and effective risk measurement and mitigation via a centralized dashboard. The platform provides a smart, standardized solution for managing privacy risks and ensures that data can be effectively transformed for safe use right across your business ecosystem. Access dynamic recommendations for data transformation and view privacy-utility impact simulations before performing forensically targeted de-identification to mitigate risks. Transform data to create privacy-enhanced datasets that can be shared or transferred and used responsibly by teams.

Apache Doris is a modern data warehouse for real-time analytics. It delivers lightning-fast analytics on real-time data at scale. Push-based micro-batch and pull-based streaming data ingestion within a second. Storage engine with real-time upsert, append and pre-aggregation. Optimize for high-concurrency and high-throughput queries with columnar storage engine, MPP architecture, cost based query optimizer, vectorized execution engine. Federated querying of data lakes such as Hive, Iceberg and Hudi, and databases such as MySQL and PostgreSQL. Compound data types such as Array, Map and JSON. Variant data type to support auto data type inference of JSON data. NGram bloomfilter and inverted index for text searches. Distributed design for linear scalability. Workload isolation and tiered storage for efficient resource management. Supports shared-nothing clusters as well as separation of storage and compute.

Rclone is a command-line program to manage files on cloud storage. It is a feature-rich alternative to cloud vendors' web storage interfaces. Over 40 cloud storage products support rclone including S3 object stores, business & consumer file storage services, as well as standard transfer protocols. Rclone has powerful cloud equivalents to the Unix commands rsync, cp, mv, mount, ls, ncdu, tree, rm, and cat. Rclone's familiar syntax includes shell pipeline support, and --dry-run protection. It is used at the command line, in scripts, or via its API. Rclone really looks after your data. It preserves timestamps and verifies checksums at all times. Transfers over limited bandwidth; intermittent connections, or subject to quota can be restarted, from the last good file transferred. You can check the integrity of your files. Where possible, rclone employs server-side transfers to minimize local bandwidth use and transfers from one provider to another without using the local disk.

See the impact of data issues without running SQL. We analyze your logs and metadata to identify freshness and volume anomalies, schema changes in tables, pipeline errors, and their blast radius effects on your business. Masthead observes every table, process, script, and dashboard in the data warehouse and connected BI tools for anomalies, alerting data teams in real time if any data failures occur. Masthead shows the origin and implications of data anomalies and pipeline errors on data consumers. Masthead maps data issues on lineage, so you can troubleshoot within minutes, not hours. We get a comprehensive view of all processes in GCP without giving access to our data was a game-changer for us. It saved us both time and money. Gain visibility into the cost of each pipeline running in your cloud, regardless of ETL. Masthead also has AI-powered recommendations to help you optimize your models and queries. It takes 15 min to connect Masthead to all assets in your data warehouse.

Sprucely.io is a flexible platform service that automates your data insights pipeline. It takes data from a multitude of sources and creates interactive decision intelligence to share or integrate with your services in seconds. Central to the concept of Sprucely is a modern web architecture and a platform service that define, store, and serve datasets and dashboards. You can see Sprucely as the engine that controls the data pipeline and all the associated infrastructure. It will seamlessly serve users, your Web pages, and your document resources with the data intelligence reports that you decide to share. But Sprucely is a lot more. It automatically generates data intelligence based on the context you provide. It is an ecosystem where you can use Connector applications to integrate with your favourite productivity tools such as Microsoft Powerpoint. Or you can create your own integration to Sprucely using REST APIs.

Self-serve your company's data insights with AI. Fluent is your AI data analyst, it helps you explore your data and uncover the questions you should be asking. No complicated UI and no learning curve; just type in your question and Fluent will do the rest. Fluent works with you to clarify your question, so you can get the insight you need. With Fluent, you can uncover the questions you should be asking to get more out of your data. Fluent lets you build a shared understanding of your data, with real-time collaboration and a shared data dictionary. No more silos, no more confusion, and no more disagreements on how to define revenue. Fluent integrates with Slack and Teams, so you can get data insights without leaving your chat. Fluent gives verifiable output with a visual display of the exact SQL journey and AI logic for each query. Curate tailored datasets with clear usage guidelines and quality control, enhancing data integrity and access management.

Qubole is a simple, open, and secure Data Lake Platform for machine learning, streaming, and ad-hoc analytics. Our platform provides end-to-end services that reduce the time and effort required to run Data pipelines, Streaming Analytics, and Machine Learning workloads on any cloud. No other platform offers the openness and data workload flexibility of Qubole while lowering cloud data lake costs by over 50 percent. Qubole delivers faster access to petabytes of secure, reliable and trusted datasets of structured and unstructured data for Analytics and Machine Learning. Users conduct ETL, analytics, and AI/ML workloads efficiently in end-to-end fashion across best-of-breed open source engines, multiple formats, libraries, and languages adapted to data volume, variety, SLAs and organizational policies.

The Ocient Hyperscale Data Warehouse transforms and loads data in seconds, enables organizations to store and analyze more data, and executes queries on hyperscale datasets up to 50x faster. To deliver next-generation data analytics, Ocient completely reimagined its data warehouse design to deliver rapid, continuous analysis of complex, hyperscale datasets. The Ocient Hyperscale Data Warehouse brings storage adjacent to compute to maximize performance on industry-standard hardware, enables users to transform, stream or load data directly, and returns previously infeasible queries in seconds. Optimized for industry standard hardware, Ocient has benchmarked query performance levels up to 50x better than competing products. The Ocient Hyperscale Data Warehouse empowers next-generation data analytics solutions in key areas where existing solutions fall short.

Cloudera DataFlow for the Public Cloud (CDF-PC) is a cloud-native universal data distribution service powered by Apache NiFi ​​that lets developers connect to any data source anywhere with any structure, process it, and deliver to any destination. CDF-PC offers a flow-based low-code development paradigm that aligns best with how developers design, develop, and test data distribution pipelines. With over 400+ connectors and processors across the ecosystem of hybrid cloud services—including data lakes, lakehouses, cloud warehouses, and on-premises sources—CDF-PC provides indiscriminate data distribution. These data distribution flows can then be version-controlled into a catalog where operators can self-serve deployments to different runtimes.