Pantomath Alternatives

(Bank CFO) “I don’t have confidence and trust in our data. We keep discovering hidden risks”. Since 70% of data initiatives fail due to unreliable data (Gartner research), are you risking your reputation by trusting the accuracy of your data that you share with your business stakeholders and partners? Data Trust Scores must be measured in Data Lakes, warehouses, and throughout the pipeline, to ensure the data is trustworthy and fit for use. It typically takes 4-6 weeks of manual effort just to set a file or table for validation. Then, the rules have to be constantly updated as the data evolves. The only scalable option is to automate data validation rules discovery and rules maintenance. DataBuck is an autonomous, self-learning, Data Observability, Quality, Trustability and Data Matching tool. It reduces effort by 90% and errors by 70%. "What took my team of 10 Engineers 2 years to do, DataBuck could complete it in less than 8 hours." (VP, Enterprise Data Office, a US bank)

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.

Rivery’s SaaS ETL platform provides a fully-managed solution for data ingestion, transformation, orchestration, reverse ETL and more, with built-in support for your development and deployment lifecycles. Key Features: Data Workflow Templates: Extensive library of pre-built templates that enable teams to instantly create powerful data pipelines with the click of a button. Fully managed: No-code, auto-scalable, and hassle-free platform. Rivery takes care of the back end, allowing teams to spend time on priorities rather than maintenance. Multiple Environments: Construct and clone custom environments for specific teams or projects. Reverse ETL: Automatically send data from cloud warehouses to business applications, marketing clouds, CPD’s, and more.

Monitor and control everything your data pipelines do with zero code changes. Monitor data and pipelines in motion to proactively prevent downtime and quickly root cause issues. Optimize pipeline runs and job performance to save costs and keep SLAs. Accelerate code deployments and platform upgrades while maintaining reliability and performance. Data & performance checks in line with pipeline runs. Checks on input data, before pipelines even run. Automatic preemption of runs. definity takes away the effort to build deep end-to-end coverage, so you are protected at every step, across every dimension. definity shifts observability to post-production to achieve ubiquity, increase coverage, and reduce manual effort. definity agents automatically run with every pipeline, with zero footprints. Unified view of data, pipelines, infra, lineage, and code for every data asset. Detect in run-time and avoid async checks. Auto-preempt runs, even on inputs.

Castor is a data catalog designed for mass adoption across the whole company. Have an overview of all your data environment. Search for data instantly thanks to our powerful search engine. Onboard to a new data infrastructure and access data in a breeze. Go beyond your traditional data catalog. Modern data teams now have numerous data sources, build one truth. With its delightful and automated documentation experience, Castor makes it dead simple to trust data. Column-level, cross-system data lineage in minutes. Get a bird’s eye view of your data pipelines to build trust in your data. Troubleshoot data issues, perform impact analyses, comply with GDPR in one tool. Optimize performance, cost, compliance, and security for your data. Keep your data stack healthy with our automated infrastructure monitoring system.

Improving the experience, efficiency, and profitability of streaming video requires data. Datazoom enables video publishers to better operate distributed architectures through centralizing, standardizing, and integrating data in real-time to create a more powerful data pipeline and improve observability, adaptability, and optimization solutions. Datazoom is a video data platform that continually gathers data from endpoints, like a CDN or a video player, through an ecosystem of collectors. Once the data is gathered, it is normalized using standardized data definitions. This data is then sent through available connectors to analytics platforms like Google BigQuery, Google Analytics, and Splunk and can be visualized in tools such as Looker and Superset. Datazoom is your key to a more effective and efficient data pipeline. Get the data you need in real-time. Don’t wait for your data when you need to resolve an issue immediately.

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.

StreamSets DataOps Platform. The data integration platform to build, run, monitor and manage smart data pipelines that deliver continuous data for DataOps, and power modern analytics and hybrid integration. Only StreamSets provides a single design experience for all design patterns for 10x greater developer productivity; smart data pipelines that are resilient to change for 80% less breakages; and a single pane of glass for managing and monitoring all pipelines across hybrid and cloud architectures to eliminate blind spots and control gaps. With StreamSets, you can deliver the continuous data that drives the connected enterprise.

Unify Your Data Stack: Experience the first no-code data pipeline platform and power enlightened decision making. Integrate.io is the only complete set of data solutions & connectors for easy building and managing of clean, secure data pipelines. Increase your data team's output with all of the simple, powerful tools & connectors you’ll ever need in one no-code data integration platform. Empower any size team to consistently deliver projects on-time & under budget. We ensure your success by partnering with you to truly understand your needs & desired outcomes. Our only goal is to help you overachieve yours. Integrate.io's Platform includes: -No-Code ETL & Reverse ETL: Drag & drop no-code data pipelines with 220+ out-of-the-box data transformations -Easy ELT & CDC :The Fastest Data Replication On The Market -Automated API Generation: Build Automated, Secure APIs in Minutes - Data Warehouse Monitoring: Finally Understand Your Warehouse Spend - FREE Data Observability: Custom

Hevo Data is a no-code, bi-directional data pipeline platform specially built for modern ETL, ELT, and Reverse ETL Needs. It helps data teams streamline and automate org-wide data flows that result in a saving of ~10 hours of engineering time/week and 10x faster reporting, analytics, and decision making. The platform supports 100+ ready-to-use integrations across Databases, SaaS Applications, Cloud Storage, SDKs, and Streaming Services. Over 500 data-driven companies spread across 35+ countries trust Hevo for their data integration needs. Try Hevo today and get your fully managed data pipelines up and running in just a few minutes.

For data teams looking to increase the availability of trusted data, Astronomer provides Astro, a modern data orchestration platform, powered by Apache Airflow, that enables the entire data team to build, run, and observe data pipelines-as-code. Astronomer is the commercial developer of Airflow, the de facto standard for expressing data flows as code, used by hundreds of thousands of teams across the world.

Reclaim control of your data pipelines and deliver value instantly, without errors. The DataKitchen™ DataOps platform automates and coordinates all the people, tools, and environments in your entire data analytics organization – everything from orchestration, testing, and monitoring to development and deployment. You’ve already got the tools you need. Our platform automatically orchestrates your end-to-end multi-tool, multi-environment pipelines – from data access to value delivery. Catch embarrassing and costly errors before they reach the end-user by adding any number of automated tests at every node in your development and production pipelines. Spin-up repeatable work environments in minutes to enable teams to make changes and experiment – without breaking production. Fearlessly deploy new features into production with the push of a button. Free your teams from tedious, manual work that impedes innovation.

Dagster is a next-generation orchestration platform for the development, production, and observation of data assets. Unlike other data orchestration solutions, Dagster provides you with an end-to-end development lifecycle. Dagster gives you control over your disparate data tools and empowers you to build, test, deploy, run, and iterate on your data pipelines. It makes you and your data teams more productive, your operations more robust, and puts you in complete control of your data processes as you scale. Dagster brings a declarative approach to the engineering of data pipelines. Your team defines the data assets required, quickly assessing their status and resolving any discrepancies. An assets-based model is clearer than a tasks-based one and becomes a unifying abstraction across the whole workflow.

Automate self-service provisioning and refresh of enterprise workloads, integrate with existing toolchain. High-performance data delivery and re-use for data scientists through a rich set of APIs and automation. Recover any data across any cloud from any point in time – at the same time – at scale, beyond legacy solutions. Minimize the business impact of ransomware / cyber attacks by recovering quickly with immutable backups. Unified platform to better protect, secure, retain, govern, or recover your data on-premises or in the cloud. Actifio’s patented software platform turns data silos into data pipelines. Virtual Data Pipeline (VDP) delivers full-stack data management — on-premises, hybrid or multi-cloud – from rich application integration, SLA-based orchestration, flexible data movement, and data immutability and security.

DataOps.live, the Data Products company, delivers productivity and governance breakthroughs for data developers and teams through environment automation, pipeline orchestration, continuous testing and unified observability. We bring agile DevOps automation and a powerful unified cloud Developer Experience (DX) ​to modern cloud data platforms like Snowflake.​ DataOps.live, a global cloud-native company, is used by Global 2000 enterprises including Roche Diagnostics and OneWeb to deliver 1000s of Data Product releases per month with the speed and governance the business demands.

Spectra is a comprehensive DataOps (data ingestion, transformation, and preparation) platform to build and manage complex, varied data pipelines using a low-code user interface with domain-specific features to deliver data solutions at speed and at scale. Maximize your ROI with faster time-to-market and time-to-value, and reduced cost of ownership. Get access to over 50 pre-built native connectors with readily available data processing functions such as sort, look-up, join, transform, grouping and many more. Process structured, semi-structured, and unstructured data in batch or real-time streaming data. Optimize and control infrastructure spending for your organization by efficiently managing data processing and data pipeline. Spectra’s pushdown transformation capabilities with Snowflake Data Cloud enables enterprises to leverage Snowflake’s high-performing processing power and scalable architecture.

A high -performance unified platform which is layered on any existing infrastructure for seamless onboarding. Metrolink’s intuitive design empowers any organization to govern its data integration by arming it with advanced manipulations aimed to maximize diverse and complex data, refocus human resources, and ​eliminate overhead. Diverse, complex, multi-source, streaming data with rapidly changing use cases. Spending much more of the talent on data utilities, losing the focus on the core business. Metrolink is a Unified platform that allows organization design and manage their data pipelines according to their business requirements. This by enabling intuitive UI, advanced manipulations on diverse & complex data with high performance, in a way that amplifies data value while leveraging all data functions and data privacy in the organization.

CData Sync is a universal data pipeline that delivers automated continuous replication between hundreds of SaaS applications & cloud data sources and any major database or data warehouse, on-premise or in the cloud. Replicate data from hundreds of cloud data sources to popular database destinations, such as SQL Server, Redshift, S3, Snowflake, BigQuery, and more. Configuring replication is easy: login, select the data tables to replicate, and select a replication interval. Done. CData Sync extracts data iteratively, causing minimal impact on operational systems by only querying and updating data that has been added or changed since the last update. CData Sync offers the utmost flexibility across full and partial replication scenarios and ensures that critical data is stored safely in your database of choice. Download a 30-day free trial of the Sync application or request more information at www.cdata.com/sync

Connecting systems to scale AI initiatives is complex, expensive, and prone to fail. Pandio’s cloud-native managed solution simplifies your data pipelines to harness the power of AI. Access your data from anywhere at any time in order to query, analyze, and drive to insight. Big data analytics without the big cost. Enable data movement seamlessly. Streaming, queuing and pub-sub with unmatched throughput, latency, and durability. Design, train, and deploy machine learning models locally in less than 30 minutes. Accelerate your path to ML and democratize the process across your organization. And it doesn’t require months (or years) of disappointment. Pandio’s AI-driven architecture automatically orchestrates your models, data, and ML tools. Pandio works with your existing stack to accelerate your ML initiatives. Orchestrate your models and messages across your organization.

The fastest way to prep data and build data pipelines in the cloud. Trifacta provides visual and intelligent guidance to accelerate data preparation so you can get to insights faster. Poor data quality can sink any analytics project. Trifacta helps you understand your data so you can quickly and accurately clean it up. All the power with none of the code. Trifacta provides visual and intelligent guidance so you can get to insights faster. Manual, repetitive data preparation processes don’t scale. Trifacta helps you build, deploy and manage self-service data pipelines in minutes not months.

Data-driven computational pipelines. Nextflow enables scalable and reproducible scientific workflows using software containers. It allows the adaptation of pipelines written in the most common scripting languages. Its fluent DSL simplifies the implementation and deployment of complex parallel and reactive workflows on clouds and clusters. Nextflow is built around the idea that Linux is the lingua franca of data science. Nextflow allows you to write a computational pipeline by making it simpler to put together many different tasks. You may reuse your existing scripts and tools and you don't need to learn a new language or API to start using it. Nextflow supports Docker and Singularity containers technology. This, along with the integration of the GitHub code-sharing platform, allows you to write self-contained pipelines, manage versions, and rapidly reproduce any former configuration. Nextflow provides an abstraction layer between your pipeline's logic and the execution layer.

More data sources, more silos, more complexity, and constant change. Data architectures are challenged to keep pace—a big problem for today's data-driven organizations, and one that puts your business at risk. A data fabric is a modern distributed data architecture that includes shared data assets and optimized data fabric pipelines that you can use to address today's data challenges in a unified way. Optimized data management and integration capabilities so you can intelligently simplify, automate, and accelerate your data pipelines. Easy-to-deploy and adapt distributed data architecture that fits your complex, ever-changing technology landscape. Accelerate time to value by unlocking your distributed on-premises, cloud, and hybrid cloud data, no matter where it resides, and delivering it wherever it's needed at the pace of business.

Uncover insights to supercharge sales growth using code-free, fully-automated data pipelines to data lakes or cloud warehouses. A flexible, standards-based platform to unify sales and marketing data for automating insights and smarter growth. Say goodbye to messy, expensive manual data downloads. Always know what you’ll pay and only pay for what you use. Fuel your tools with quick access to analytics-ready data. As certified developers, we only work with secure, official APIs. Get started quickly with data pipelines from popular sources. Pre-built, pre-transformed, and ready-to-go data pipelines. Unlock data from Amazon Vendor Central, Amazon Seller Central, Instagram Stories, Facebook, Amazon Advertising, Google Ads, and many others. Code-free data ingestion and transformation processes allow teams to realize value from their data quickly and cost-effectively. Data is always securely stored directly in a trusted, customer-owned data destination like Databricks, Amazon Redshift, etc.

Microservice-based streaming and batch data processing for Cloud Foundry and Kubernetes. Spring Cloud Data Flow provides tools to create complex topologies for streaming and batch data pipelines. The data pipelines consist of Spring Boot apps, built using the Spring Cloud Stream or Spring Cloud Task microservice frameworks. Spring Cloud Data Flow supports a range of data processing use cases, from ETL to import/export, event streaming, and predictive analytics. The Spring Cloud Data Flow server uses Spring Cloud Deployer, to deploy data pipelines made of Spring Cloud Stream or Spring Cloud Task applications onto modern platforms such as Cloud Foundry and Kubernetes. A selection of pre-built stream and task/batch starter apps for various data integration and processing scenarios facilitate learning and experimentation. Custom stream and task applications, targeting different middleware or data services, can be built using the familiar Spring Boot style programming model.

At K2View, we believe that every enterprise should be able to leverage its data to become as disruptive and agile as the best companies in its industry. We make this possible through our patented Data Product Platform, which creates and manages a complete and compliant dataset for every business entity – on demand, and in real time. The dataset is always in sync with its underlying sources, adapts to changes in the source structures, and is instantly accessible to any authorized data consumer. Data Product Platform fuels many operational use cases, including customer 360, data masking and tokenization, test data management, data migration, legacy application modernization, data pipelining and more – to deliver business outcomes in less than half the time, and at half the cost, of any other alternative. The platform inherently supports modern data architectures – data mesh, data fabric, and data hub – and deploys in cloud, on-premise, or hybrid environments.

Lightbend provides technology that enables developers to easily build data-centric applications that bring the most demanding, globally distributed applications and streaming data pipelines to life. Companies worldwide turn to Lightbend to solve the challenges of real-time, distributed data in support of their most business-critical initiatives. Akka Platform provides the building blocks that make it easy for businesses to build, deploy, and run large-scale applications that support digitally transformative initiatives. Accelerate time-to-value and reduce infrastructure and cloud costs with reactive microservices that take full advantage of the distributed nature of the cloud and are resilient to failure, highly efficient, and operative at any scale. Native support for encryption, data shredding, TLS enforcement, and continued compliance with GDPR. Framework for quick construction, deployment and management of streaming data pipelines.

Cloud Composer's managed nature and Apache Airflow compatibility allows you to focus on authoring, scheduling, and monitoring your workflows as opposed to provisioning resources. End-to-end integration with Google Cloud products including BigQuery, Dataflow, Dataproc, Datastore, Cloud Storage, Pub/Sub, and AI Platform gives users the freedom to fully orchestrate their pipeline. Author, schedule, and monitor your workflows through a single orchestration tool—whether your pipeline lives on-premises, in multiple clouds, or fully within Google Cloud. Ease your transition to the cloud or maintain a hybrid data environment by orchestrating workflows that cross between on-premises and the public cloud. Create workflows that connect data, processing, and services across clouds to give you a unified data environment.

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.

Unravel makes data work anywhere: on Azure, AWS, GCP or in your own data center– Optimizing performance, automating troubleshooting and keeping costs in check. Unravel helps you monitor, manage, and improve your data pipelines in the cloud and on-premises – to drive more reliable performance in the applications that power your business. Get a unified view of your entire data stack. Unravel collects performance data from every platform, system, and application on any cloud then uses agentless technologies and machine learning to model your data pipelines from end to end. Explore, correlate, and analyze everything in your modern data and cloud environment. Unravel’s data model reveals dependencies, issues, and opportunities, how apps and resources are being used, what’s working and what’s not. Don’t just monitor performance – quickly troubleshoot and rapidly remediate issues. Leverage AI-powered recommendations to automate performance improvements, lower costs, and prepare.

Use cutting-edge data science tools to transform your business outcomes. SynctacticAI crafts a successful adventure out of your business by leveraging advanced data science tools, algorithms and systems to extract knowledge and insights from any structured and unstructured sets of data. Discover your data in any form – structure or unstructured and batch or real-time.Sync Discover is a key feature to discover a relevant piece of data and organizing the large pool of data in a systematic manner. Process your data at scale with Sync Data. Enabled with a simple navigation interface like drag and drop, you can smoothly configure your data pipelines and process data manually or at predetermined schedules. With the power of machine learning, the process of learning from data becomes effortless. Simply select the target variable, feature, and any of our pre-built models – rest is automatically taken care of by Sync Learn.

Integrate unstructured external data into your organization in minutes. Datastreamer is a turnkey data platform to source, unify, and enrich unstructured external data with 95% less work than building pipelines in-house. Customers use Datastreamer to feed specialized AI models and accelerate insights in Threat Intelligence, KYC/AML, Financial Analysis and more. Feed your analytics products or specialized AI models with billions of data pieces from social media, blogs, news, forums, dark web data, and more. Our platform unifies source data into a common schema so you can use content from multiple sources simultaneously. Leverage our pre-integrated data partners or connect data from any data supplier. Tap into our powerful AI models to enhance data with components like sentiment analysis and PII redaction. Scale data pipelines with less costs by plugging into our managed infrastructure that is optimized to handle massive volumes of text data.

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.

Design, debug, run and troubleshoot data transformations and jobflows in a developer-friendly visual designer. Orchestrate data workloads that require tasks to be carried out in the right sequence, orchestrate multiple systems with the transparency of visual workflows. Deploy data workloads easily into a robust enterprise runtime environment. In cloud or on-premise. Make data available to people, applications and storage under a single unified platform. Manage your data workloads and related processes together in a single platform. No task is too complex. We’ve built CloverDX on years of experience with large enterprise projects. Developer-friendly open architecture and flexibility lets you package and hide the complexity for non-technical users. Manage the entire lifecycle of a data pipeline from design, deployment to evolution and testing. Get things done fast with the help of our in-house customer success teams.

Datameer revolutionizes data transformation with a low-code approach, trusted by top global enterprises. Craft, transform, and publish data seamlessly with no code and SQL, simplifying complex data engineering tasks. Empower your data teams to make informed decisions confidently while saving costs and ensuring responsible self-service analytics. Speed up your analytics workflow by transforming datasets to answer ad-hoc questions and support operational dashboards. Empower everyone on your team with our SQL or Drag-and-Drop to transform your data in an intuitive and collaborative workspace. And best of all, everything happens in Snowflake. Datameer is designed and optimized for Snowflake to reduce data movement and increase platform adoption. Some of the problems Datameer solves: - Analytics is not accessible - Drowning in backlog - Long development

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

StreamNative redefines streaming infrastructure by seamlessly integrating Kafka, MQ, and other protocols into a single, unified platform, providing unparalleled flexibility and efficiency for modern data processing needs. StreamNative offers a unified solution that adapts to the diverse requirements of streaming and messaging in a microservices-driven environment. By providing a comprehensive and intelligent approach to messaging and streaming, StreamNative empowers organizations to navigate the complexities and scalability of the modern data ecosystem with efficiency and agility. Apache Pulsar’s unique architecture decouples the message serving layer from the message storage layer to deliver a mature cloud-native data-streaming platform. Scalable and elastic to adapt to rapidly changing event traffic and business needs. Scale-up to millions of topics with architecture that decouples computing and storage.

In-Memory Computing Platform. The digital world is different. Microseconds matter. That's why the world's largest organizations rely on us to power their most time-sensitive applications at scale. New data-enabled applications can deliver transformative business power – if they meet today’s requirement of immediacy. Hazelcast solutions complement virtually any database to deliver results that are significantly faster than a traditional system of record. Hazelcast’s distributed architecture provides redundancy for continuous cluster up-time and always available data to serve the most demanding applications. Capacity grows elastically with demand, without compromising performance or availability. The fastest in-memory data grid, combined with third-generation high-speed event processing, delivered through the cloud.

AWS Data Pipeline is a web service that helps you reliably process and move data between different AWS compute and storage services, as well as on-premises data sources, at specified intervals. With AWS Data Pipeline, you can regularly access your data where it’s stored, transform and process it at scale, and efficiently transfer the results to AWS services such as Amazon S3, Amazon RDS, Amazon DynamoDB, and Amazon EMR. AWS Data Pipeline helps you easily create complex data processing workloads that are fault tolerant, repeatable, and highly available. You don’t have to worry about ensuring resource availability, managing inter-task dependencies, retrying transient failures or timeouts in individual tasks, or creating a failure notification system. AWS Data Pipeline also allows you to move and process data that was previously locked up in on-premises data silos.

Upsolver makes it incredibly simple to build a governed data lake and to manage, integrate and prepare streaming data for analysis. Define pipelines using only SQL on auto-generated schema-on-read. Easy visual IDE to accelerate building pipelines. Add Upserts and Deletes to data lake tables. Blend streaming and large-scale batch data. Automated schema evolution and reprocessing from previous state. Automatic orchestration of pipelines (no DAGs). Fully-managed execution at scale. Strong consistency guarantee over object storage. Near-zero maintenance overhead for analytics-ready data. Built-in hygiene for data lake tables including columnar formats, partitioning, compaction and vacuuming. 100,000 events per second (billions daily) at low cost. Continuous lock-free compaction to avoid “small files” problem. Parquet-based tables for fast queries.

The only all-in-one data pipeline platform. Built ground-up for a cloud-first world, Gathr is the only platform to handle all your data integration and engineering needs - ingestion, ETL, ELT, CDC, streaming analytics, data preparation, machine learning, advanced analytics and more. With Gathr, anyone can build and deploy pipelines in minutes, irrespective of skill levels. Create Ingestion pipelines in minutes, not weeks. Ingest data from any source, deliver to any destination. Build applications quickly with a wizard-based approach. Replicate data in real-time using a templatized CDC app. Native integration for all sources and targets. Best-in-class capabilities with everything you need to succeed today and tomorrow. Choose between free, pay-per-use or customize as per your requirements.

You select the size of the cluster, node capacity, and a set of services, and Yandex Data Proc automatically creates and configures Spark and Hadoop clusters and other components. Collaborate by using Zeppelin notebooks and other web apps via a UI proxy. You get full control of your cluster with root permissions for each VM. Install your own applications and libraries on running clusters without having to restart them. Yandex Data Proc uses instance groups to automatically increase or decrease computing resources of compute subclusters based on CPU usage indicators. Data Proc allows you to create managed Hive clusters, which can reduce the probability of failures and losses caused by metadata unavailability. Save time on building ETL pipelines and pipelines for training and developing models, as well as describing other iterative tasks. The Data Proc operator is already built into Apache Airflow.

Y42 is the first fully managed Modern DataOps Cloud. It is purpose-built to help companies easily design production-ready data pipelines on top of their Google BigQuery or Snowflake cloud data warehouse. Y42 provides native integration of best-of-breed open-source data tools, comprehensive data governance, and better collaboration for data teams. With Y42, organizations enjoy increased accessibility to data and can make data-driven decisions quickly and efficiently.

Data Prep Runner (DPR) by QVIKPREP simplifies data prepping and streamlines data processing. Improve your business processes, easily compare data, and enhance data profiling. Save time prepping data for operational reporting, data analysis, and moving data between systems. Reduce risk on data integration project timelines and catch issues early through data profiling. Increase productivity for operations teams by automating data processing. Manage data prep easily and build a robust data pipeline. DPR provides checks based on past data for better accuracy. Drive transactions into your systems and use data to drive data driven test automation. DPR gets data where it needs to end up. Ensure data integration projects deliver on time. Uncover and tackle data issues early, instead of during test cycles. Validate your data with rules and repair data in the data pipeline. DPR makes comparing data between sources efficient with color-coded reports.

Powerful data engineering workflows, without the infrastructure headaches. Complex streaming, scheduling, and data backfill pipelines, are all defined in simple, composable Python. Make ETL a thing of the past, fetch all of your data in real-time, no matter how complex. Incorporate deep learning and LLMs into decisions alongside structured business data. Make better predictions with fresher data, don’t pay vendors to pre-fetch data you don’t use, and query data just in time for online predictions. Experiment in Jupyter, then deploy to production. Prevent train-serve skew and create new data workflows in milliseconds. Instantly monitor all of your data workflows in real-time; track usage, and data quality effortlessly. Know everything you computed and data replay anything. Integrate with the tools you already use and deploy to your own infrastructure. Decide and enforce withdrawal limits with custom hold times.

Automate your business pipeline with our flow builder. Use operations that matters to you. Bring your own service providers for email, sms and http services. Use our advanced query builder to query and analyze csv with any field numbers and rows. We store the csv files you've uploaded on our platform in a secured vault and account activity logs. We don't store any data records you request for processing.

Montara enables BI teams and data analysts, using SQL only, to model and transform their data easily and seamlessly and enjoy benefits such as modular code, CI/CD, versioning and automated testing and documentation. With Montara, analysts can quickly understand how changes to models impact analysis, reports and dashboards with report-level lineage and support for 3rd party visualization tools such as Tableau and Looker. Furthermore, BI teams can perform ad-hoc analysis and create reports and dashboards on Montara directly.

Tarsal's infinite scalability means as your organization grows, Tarsal grows with you. Tarsal makes it easy for you to switch where you're sending data - today's SIEM data is tomorrow's data lake data; all with one click. Keep your SIEM and gradually migrate analytics over to a data lake. You don't have to rip anything out to use Tarsal. Some analytics just won't run on your SIEM. Use Tarsal to have query-ready data on a data lake. Your SIEM is one of the biggest line items in your budget. Use Tarsal to send some of that data to your data lake. Tarsal is the first highly scalable ETL data pipeline built for security teams. Easily exfil terabytes of data in just just a few clicks, with instant normalization, and route that data to your desired destination.

Make use of Reactive Programming on the back-end without the need for specialized languages or cumbersome frameworks. Triggers, Actors and Event Collections make it easy to build data pipelines and work with data streams using simple SQL-like syntax, shielding users from the complexities of distributed system development. Extensible Data Modeling is a key feature that supports rich semantics and schema definition for representing real-world things. On-the-fly validation and data shaping rules support a variey of formats like XML and JSON, allowing you to easily describe and evolve your schema, keeping pace with changing business requirements. If you can describe it, we can query it. Know SQL and Javascript? Then you already know how to use the data engine. Whatever the format, a powerful query language lets you instantly test logic expressions and functions, speeding up development and simplifying deployment for unmatched data agility.

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.

Embed sensors for IoT use cases and enrich sensor data with control system and environment data. Integrate this in real time with enterprise data and deploy predictive algorithms to discover new insights and harvest your data for meaningful use. Use analytics to predict maintenance problems, understand asset utilization, reduce defects and optimize processes. Harness the power of connected devices to deliver remote monitoring and diagnostics services. Employ IoT Analytics to predict safety hazards and comply with regulations to reduce worksite accidents. Lumada Data Integration: Rapidly build and deploy data pipelines at scale. Integrate data from lakes, warehouses and devices, and orchestrate data flows across all environments. By building ecosystems with customers and business partners in various business areas, we can accelerate digital innovation to create new value for a new society.