Oarkflow 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)

Fivetran is the smartest way to replicate data into your warehouse. We've built the only zero-maintenance pipeline, turning months of on-going development into a 5-minute setup. Our connectors bring data from applications and databases into one central location so that analysts can unlock profound insights about their business. Schema designs and ERDs make synced data immediately usable. Transform data into analytics-ready tables as soon as it’s loaded into your warehouse. Spend less time writing transformation code with our out-of-the-box data modeling. Connect to any git repository and manage dbt models directly from Fivetran. Develop and deliver your product with the utmost confidence in ours. Uptime and data delivery guarantees ensure your customers’ data never goes stale. Troubleshoot fast with a global team of Support Specialists.

Alooma enables data teams to have visibility and control. It brings data from your various data silos together into BigQuery, all in real time. Set up and flow data in minutes or customize, enrich, and transform data on the stream before it even hits the data warehouse. Never lose an event. Alooma's built in safety nets ensure easy error handling without pausing your pipeline. Any number of data sources, from low to high volume, Alooma’s infrastructure scales to your needs.

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

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.

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.

Panoply brings together a managed data warehouse with included, pre-built ELT data connectors, making it the easiest way to store, sync, and access all your business data. Our cloud data warehouse (built on Redshift or BigQuery), along with built-in data integrations to all major CRMs, databases, file systems, ad networks, web analytics tools, and more, will have you accessing usable data in less time, with a lower total cost of ownership. One platform with one easy price is all you need to get your business data up and running today. Panoply gives you unlimited access to data sources with prebuilt Snap Connectors and a Flex Connector that can bring in data from nearly any RestAPI. Panoply can be set up in minutes, requires zero ongoing maintenance, and provides online support including access to experienced data architects.

Centralize offline data, import files, process and clean up data. Export to a live database with 1 click. Streamline data workflows. Centralize offline data and make it accessible to your team. Bring offline files to Dropbase. Multiple formats. Any way you like. Process and format data. Add, edit, re-order, and delete processing steps. 1-click exports. Export to database, endpoints, or download code with 1 click. Instant REST API access. Query Dropbase data securely with REST API access keys. Onboard data where you need it. Combine and process datasets to fit the desired format or data model. No code. Process your data pipelines using a spreadsheet interface. Track every step. Flexible. Use a library of pre-built processing functions. Or write your own. 1-click exports. Export to database or generate endpoints with 1 click. Manage databases. Manage and databases and credentials.

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.

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.

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.

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.

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.

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.

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.

RudderStack is the smart customer data pipeline. Easily build pipelines connecting your whole customer data stack, then make them smarter by pulling analysis from your data warehouse to trigger enrichment and activation in customer tools for identity stitching and other advanced use cases. Start building smarter customer data pipelines today.

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.

Stripe Data Pipeline sends all your up-to-date Stripe data and reports to Snowflake or Amazon Redshift in a few clicks. Centralize your Stripe data with other business data to close your books faster and unlock richer business insights. Set up Stripe Data Pipeline in minutes and automatically receive your Stripe data and reports in your data warehouse on an ongoing basis–no code required. Create a single source of truth to speed up your financial close and access better insights. Identify your best-performing payment methods, analyze fraud by location, and more. Send your Stripe data directly to your data warehouse without involving a third-party extract, transform, and load (ETL) pipeline. Offload ongoing maintenance with a pipeline that’s built into Stripe. No matter how much data you have, your data is always complete and accurate. Automate data delivery at scale, minimize security risks, and avoid data outages and delays.

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.

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.

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.

Ingest, prepare, and process data pipelines at scale for AI and analytics in the cloud. Informatica’s comprehensive data engineering portfolio provides everything you need to process and prepare big data engineering workloads to fuel AI and analytics: robust data integration, data quality, streaming, masking, and data preparation capabilities. Rapidly build intelligent data pipelines with CLAIRE®-powered automation, including automatic change data capture (CDC) Ingest thousands of databases and millions of files, and streaming events. Accelerate time-to-value ROI with self-service access to trusted, high-quality data. Get unbiased, real-world insights on Informatica data engineering solutions from peers you trust. Reference architectures for sustainable data engineering solutions. AI-powered data engineering in the cloud delivers the trusted, high quality data your analysts and data scientists need to transform business.

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.

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.

With Osmos, your customers can easily clean their messy data files and import them directly into your operational system without writing a line of code. At the core, we have an AI-powered data transformation engine that enables users to map, validate, and clean data with only a few clicks. Your account will be charged or credited based on the percentage of the billing cycle left at the time the plan was changed. An eCommerce company automates ingestion of product catalog data from multiple distributors and vendors into their database. A manufacturing company automates the data ingestion of purchase orders from email attachments into Netsuite. Automatically clean up and reformat incoming data to match your destination schema. Never deal with custom scripts and spreadsheets again.

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.

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.

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.

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

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.

Airflow is a platform created by the community to programmatically author, schedule and monitor workflows. Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers. Airflow is ready to scale to infinity. Airflow pipelines are defined in Python, allowing for dynamic pipeline generation. This allows for writing code that instantiates pipelines dynamically. Easily define your own operators and extend libraries to fit the level of abstraction that suits your environment. Airflow pipelines are lean and explicit. Parametrization is built into its core using the powerful Jinja templating engine. No more command-line or XML black-magic! Use standard Python features to create your workflows, including date time formats for scheduling and loops to dynamically generate tasks. This allows you to maintain full flexibility when building your workflows.

Nextflow Tower is an intuitive centralized command post that enables large-scale collaborative data analysis. With Tower, users can easily launch, manage, and monitor scalable Nextflow data analysis pipelines and compute environments on-premises or on most clouds. Researchers can focus on the science that matters rather than worrying about infrastructure engineering. Compliance is simplified with predictable, auditable pipeline execution and the ability to reliably reproduce results obtained with specific data sets and pipeline versions on demand. Nextflow Tower is developed and supported by Seqera Labs, the creators and maintainers of the open-source Nextflow project. This means that users get high-quality support directly from the source. Unlike third-party frameworks that incorporate Nextflow, Tower is deeply integrated and can help users benefit from Nextflow's complete set of capabilities.

Kestra is an open-source, event-driven orchestrator that simplifies data operations and improves collaboration between engineers and business users. By bringing Infrastructure as Code best practices to data pipelines, Kestra allows you to build reliable workflows and manage them with confidence. Thanks to the declarative YAML interface for defining orchestration logic, everyone who benefits from analytics can participate in the data pipeline creation process. The UI automatically adjusts the YAML definition any time you make changes to a workflow from the UI or via an API call. Therefore, the orchestration logic is defined declaratively in code, even if some workflow components are modified in other ways.

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.

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.

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.

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.

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.

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.

BigBI enables data specialists to build their own powerful big data pipelines interactively & efficiently, without any coding! BigBI unleashes the power of Apache Spark enabling: Scalable processing of real Big Data (up to 100X faster) Integration of traditional data (SQL, batch files) with modern data sources including semi-structured (JSON, NoSQL DBs, Elastic, Hadoop), and unstructured (Text, Audio, video), Integration of streaming data, cloud data, AI/ML & graphs

Event Hubs is a fully managed, real-time data ingestion service that’s simple, trusted, and scalable. Stream millions of events per second from any source to build dynamic data pipelines and immediately respond to business challenges. Keep processing data during emergencies using the geo-disaster recovery and geo-replication features. Integrate seamlessly with other Azure services to unlock valuable insights. Allow existing Apache Kafka clients and applications to talk to Event Hubs without any code changes—you get a managed Kafka experience without having to manage your own clusters. Experience real-time data ingestion and microbatching on the same stream. Focus on drawing insights from your data instead of managing infrastructure. Build real-time big data pipelines and respond to business challenges right away.

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.

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.

Gravity's mission is to make streaming data easy from over 100 sources while only paying for what you use. Gravity removes the reliance on engineering teams to deliver streaming pipelines with a simple interface to get streaming up and running in minutes from databases, event data and APIs. Everyone in the data team can now build with simple point and click so that you can focus on building apps, services and customer experiences. Full Execution trace and detailed error messaging for quick diagnosis and resolution. We have implemented new, feature-rich ways for you to quickly get started. From bulk set-up, default schemas and data selection to different job modes and statuses. Spend less time wrangling with infrastructure and more time analysing data while allowing our intelligent engine to keep your pipelines running. Gravity integrates with your systems for notifications and orchestration.

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.

Get all your ELT data pipelines running in minutes, even your custom ones. Let your team focus on insights and innovation. Unify your data integration pipelines in one open-source ELT platform. Airbyte addresses all your data team's connector needs, however custom they are and whatever your scale. The data integration platform that can scale with your custom or high-volume needs. From high-volume databases to the long tail of API sources. Leverage Airbyte’s long tail of high-quality connectors that adapt to schema and API changes. Extensible to unify all native & custom ELT. Edit pre-built open-source connectors, or build new ones with our connector development kit in a few hours. Transparent and scalable pricing. Finally, a transparent and predictable cost-based pricing that scales with your data needs. You don’t need to worry about volume anymore. No more need for custom systems for your in-house scripts or database replication.

Amazon Managed Workflows for Apache Airflow (MWAA) is a managed orchestration service for Apache Airflow that makes it easier to set up and operate end-to-end data pipelines in the cloud at scale. Apache Airflow is an open-source tool used to programmatically author, schedule, and monitor sequences of processes and tasks referred to as “workflows.” With Managed Workflows, you can use Airflow and Python to create workflows without having to manage the underlying infrastructure for scalability, availability, and security. Managed Workflows automatically scales its workflow execution capacity to meet your needs, and is integrated with AWS security services to help provide you with fast and secure access to data.

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.

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.

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.