Alternatives to Chalk
Compare Chalk alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Chalk in 2026. Compare features, ratings, user reviews, pricing, and more from Chalk competitors and alternatives in order to make an informed decision for your business.
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1
Teradata VantageCloud
Teradata
Teradata VantageCloud: The complete cloud analytics and data platform for AI. Teradata VantageCloud is an enterprise-grade, cloud-native data and analytics platform that unifies data management, advanced analytics, and AI/ML capabilities in a single environment. Designed for scalability and flexibility, VantageCloud supports multi-cloud and hybrid deployments, enabling organizations to manage structured and semi-structured data across AWS, Azure, Google Cloud, and on-premises systems. It offers full ANSI SQL support, integrates with open-source tools like Python and R, and provides built-in governance for secure, trusted AI. VantageCloud empowers users to run complex queries, build data pipelines, and operationalize machine learning models—all while maintaining interoperability with modern data ecosystems. -
2
Google Cloud BigQuery
Google
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. Gemini in BigQuery offers AI-driven tools for assistance and collaboration, such as code suggestions, visual data preparation, and smart recommendations designed to boost efficiency and reduce costs. BigQuery delivers an integrated platform featuring SQL, a notebook, and a natural language-based canvas interface, catering to data professionals with varying coding expertise. This unified workspace streamlines the entire analytics process. -
3
dbt
dbt Labs
dbt helps data teams transform raw data into trusted, analysis-ready datasets faster. With dbt, data analysts and data engineers can collaborate on version-controlled SQL models, enforce testing and documentation standards, lean on detailed metadata to troubleshoot and optimize pipelines, and deploy transformations reliably at scale. Built on modern software engineering best practices, dbt brings transparency and governance to every step of the data transformation workflow. Thousands of companies, from startups to Fortune 500 enterprises, rely on dbt to improve data quality and trust as well as drive efficiencies and reduce costs as they deliver AI-ready data across their organization. Whether you’re scaling data operations or just getting started, dbt empowers your team to move from raw data to actionable analytics with confidence. -
4
DataBuck
FirstEigen
DataBuck is an AI-powered data validation platform that automates risk detection across dynamic, high-volume, and evolving data environments. DataBuck empowers your teams to: ✅ Enhance trust in analytics and reports, ensuring they are built on accurate and reliable data. ✅ Reduce maintenance costs by minimizing manual intervention. ✅ Scale operations 10x faster compared to traditional tools, enabling seamless adaptability in ever-changing data ecosystems. By proactively addressing system risks and improving data accuracy, DataBuck ensures your decision-making is driven by dependable insights. Proudly recognized in Gartner’s 2024 Market Guide for #DataObservability, DataBuck goes beyond traditional observability practices with its AI/ML innovations to deliver autonomous Data Trustability—empowering you to lead with confidence in today’s data-driven world. -
5
Fivetran
Fivetran
Fivetran is a leading data integration platform that centralizes an organization’s data from various sources to enable modern data infrastructure and drive innovation. It offers over 700 fully managed connectors to move data automatically, reliably, and securely from SaaS applications, databases, ERPs, and files to data warehouses and lakes. The platform supports real-time data syncs and scalable pipelines that fit evolving business needs. Trusted by global enterprises like Dropbox, JetBlue, and Pfizer, Fivetran helps accelerate analytics, AI workflows, and cloud migrations. It features robust security certifications including SOC 1 & 2, GDPR, HIPAA, and ISO 27001. Fivetran provides an easy-to-use, customizable platform that reduces engineering time and enables faster insights. -
6
Composable DataOps Platform
Composable Analytics
Composable is an enterprise-grade DataOps platform built for business users that want to architect data intelligence solutions and deliver operational data-driven products leveraging disparate data sources, live feeds, and event data regardless of the format or structure of the data. With a modern, intuitive dataflow visual designer, built-in services to facilitate data engineering, and a composable architecture that enables abstraction and integration of any software or analytical approach, Composable is the leading integrated development environment to discover, manage, transform and analyze enterprise data.Starting Price: $8/hr - pay-as-you-go -
7
Feast
Tecton
Make your offline data available for real-time predictions without having to build custom pipelines. Ensure data consistency between offline training and online inference, eliminating train-serve skew. Standardize data engineering workflows under one consistent framework. Teams use Feast as the foundation of their internal ML platforms. Feast doesn’t require the deployment and management of dedicated infrastructure. Instead, it reuses existing infrastructure and spins up new resources when needed. You are not looking for a managed solution and are willing to manage and maintain your own implementation. You have engineers that are able to support the implementation and management of Feast. You want to run pipelines that transform raw data into features in a separate system and integrate with it. You have unique requirements and want to build on top of an open source solution. -
8
Databricks Data Intelligence Platform
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker. -
9
datuum.ai
Datuum
AI-powered data integration tool that helps streamline the process of customer data onboarding. It allows for easy and fast automated data integration from various sources without coding, reducing preparation time to just a few minutes. With Datuum, organizations can efficiently extract, ingest, transform, migrate, and establish a single source of truth for their data, while integrating it into their existing data storage. Datuum is a no-code product and can reduce up to 80% of the time spent on data-related tasks, freeing up time for organizations to focus on generating insights and improving the customer experience. With over 40 years of experience in data management and operations, we at Datuum have incorporated our expertise into the core of our product, addressing the key challenges faced by data engineers and managers and ensuring that the platform is user-friendly, even for non-technical specialists. -
10
Kestra
Kestra
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. -
11
Datameer
Datameer
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 -
12
K2View
K2View
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. -
13
Dataplane
Dataplane
The concept behind Dataplane is to make it quicker and easier to construct a data mesh with robust data pipelines and automated workflows for businesses and teams of all sizes. In addition to being more user friendly, there has been an emphasis on scaling, resilience, performance and security.Starting Price: Free -
14
Decube
Decube
Decube is a data management platform that helps organizations manage their data observability, data catalog, and data governance needs. It provides end-to-end visibility into data and ensures its accuracy, consistency, and trustworthiness. Decube's platform includes data observability, a data catalog, and data governance components that work together to provide a comprehensive solution. The data observability tools enable real-time monitoring and detection of data incidents, while the data catalog provides a centralized repository for data assets, making it easier to manage and govern data usage and access. The data governance tools provide robust access controls, audit reports, and data lineage tracking to demonstrate compliance with regulatory requirements. Decube's platform is customizable and scalable, making it easy for organizations to tailor it to meet their specific data management needs and manage data across different systems, data sources, and departments. -
15
Informatica Data Engineering
Informatica
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. -
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Ask On Data
Helical Insight
Ask On Data is a chat based AI powered open source Data Engineering/ ETL tool. With agentic capabilities and pioneering next gen data stack, Ask On Data can help in creating data pipelines via a very simple chat interface. It can be used for tasks like Data Migration, Data Loading, Data Transformations, Data Wrangling, Data Cleaning as well as Data Analysis as well with a simple chat interface. This tool can be used by Data Scientists to get clean data. Data Analyst and BI engineers to create calculated tables. Data Engineers can also use this tool to increase their efficiency and achieve much more. -
17
Google Cloud Dataflow
Google
Unified stream and batch data processing that's serverless, fast, and cost-effective. Fully managed data processing service. Automated provisioning and management of processing resources. Horizontal autoscaling of worker resources to maximize resource utilization. OSS community-driven innovation with Apache Beam SDK. Reliable and consistent exactly-once processing. Streaming data analytics with speed. Dataflow enables fast, simplified streaming data pipeline development with lower data latency. Allow teams to focus on programming instead of managing server clusters as Dataflow’s serverless approach removes operational overhead from data engineering workloads. Allow teams to focus on programming instead of managing server clusters as Dataflow’s serverless approach removes operational overhead from data engineering workloads. Dataflow automates provisioning and management of processing resources to minimize latency and maximize utilization. -
18
RudderStack
RudderStack
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.Starting Price: $750/month -
19
NAVIK AI Platform
Absolutdata Analytics
An Advanced Analytics Software Platform That Helps Sales, Marketing, Technology, and Operations Leaders Make Great Business Decisions Based on Powerful Data-Driven Insights. Addresses the breadth of AI needs across data infrastructure, data engineering and data analytics. UI, workflows and proprietary algorithms are tuned to the unique needs of each client. Components are modular enabling custom configurations. Supports, augments and automates decision making. Elimination of human biases drives better business outcomes. The AI adoption rate is unprecedented. To stay competitive, leading companies need a rapid implementation strategy that scales. To create scalable business impact, combine these four distinct capabilities. -
20
GlassFlow
GlassFlow
GlassFlow is a serverless, event-driven data pipeline platform designed for Python developers. It enables users to build real-time data pipelines without the need for complex infrastructure like Kafka or Flink. By writing Python functions, developers can define data transformations, and GlassFlow manages the underlying infrastructure, offering auto-scaling, low latency, and optimal data retention. The platform supports integration with various data sources and destinations, including Google Pub/Sub, AWS Kinesis, and OpenAI, through its Python SDK and managed connectors. GlassFlow provides a low-code interface for quick pipeline setup, allowing users to create and deploy pipelines within minutes. It also offers features such as serverless function execution, real-time API connections, and alerting and reprocessing capabilities. The platform is designed to simplify the creation and management of event-driven data pipelines, making it accessible for Python developers.Starting Price: $350 per month -
21
Vaex
Vaex
At Vaex.io we aim to democratize big data and make it available to anyone, on any machine, at any scale. Cut development time by 80%, your prototype is your solution. Create automatic pipelines for any model. Empower your data scientists. Turn any laptop into a big data powerhouse, no clusters, no engineers. We provide reliable and fast data driven solutions. With our state-of-the-art technology we build and deploy machine learning models faster than anyone on the market. Turn your data scientist into big data engineers. We provide comprehensive training of your employees, enabling you to take full advantage of our technology. Combines memory mapping, a sophisticated expression system, and fast out-of-core algorithms. Efficiently visualize and explore big datasets, and build machine learning models on a single machine. -
22
Dagster
Dagster Labs
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.Starting Price: $0 -
23
Switchboard
Switchboard
Aggregate disparate data at scale, reliably and accurately, to make better business decisions with Switchboard, a data engineering automation platform driven by business teams. Uncover timely insights and accurate forecasts. No more outdated manual reports and error-prone pivot tables that don’t scale. Directly pull and reconfigure data sources in the right formats in a no-code environment. Reduce your dependency on the engineering team. Automatic monitoring and backfilling make API outages, bad schemas, and missing data a thing of the past. Not a dumb API, but an ecosystem of pre-built connectors that are easily and quickly adapted to actively transform raw data into a strategic asset. Our team of experts has worked in data teams at Google and Facebook. We’ve automated those best practices to elevate your data game. A data engineering automation platform with authoring and workflow processes proven to scale with terabytes of data. -
24
Iterative
Iterative
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 -
25
Molecula
Molecula
Molecula is an enterprise feature store that simplifies, accelerates, and controls big data access to power machine-scale analytics and AI. Continuously extracting features, reducing the dimensionality of data at the source, and routing real-time feature changes into a central store enables millisecond queries, computation, and feature re-use across formats and locations without copying or moving raw data. The Molecula feature store provides data engineers, data scientists, and application developers a single access point to graduate from reporting and explaining with human-scale data to predicting and prescribing real-time business outcomes with all data. Enterprises spend a lot of money preparing, aggregating, and making numerous copies of their data for every project before they can make decisions with it. Molecula brings an entirely new paradigm for continuous, real-time data analysis to be used for all your mission-critical applications. -
26
Prefect
Prefect
Prefect is a workflow orchestration and automation platform designed for the modern context-driven era. It enables teams to turn Python functions into production-ready workflows with minimal effort. Prefect provides open-source foundations alongside managed platforms for enterprise-scale automation. The platform supports building and orchestrating data pipelines, workflows, and AI applications with full observability. Prefect Cloud offers managed orchestration with autoscaling, enterprise authentication, and built-in governance. Prefect Horizon extends automation to AI infrastructure by enabling deployment of MCP servers for AI agents. Trusted by leading organizations, Prefect helps teams scale automation without operational complexity. -
27
ClearML
ClearML
ClearML is the leading open source MLOps and AI platform that helps data science, ML engineering, and DevOps teams easily develop, orchestrate, and automate ML workflows at scale. Our frictionless, unified, end-to-end MLOps suite enables users and customers to focus on developing their ML code and automation. ClearML is used by more than 1,300 enterprise customers to develop a highly repeatable process for their end-to-end AI model lifecycle, from product feature exploration to model deployment and monitoring in production. Use all of our modules for a complete ecosystem or plug in and play with the tools you have. ClearML is trusted by more than 150,000 forward-thinking Data Scientists, Data Engineers, ML Engineers, DevOps, Product Managers and business unit decision makers at leading Fortune 500 companies, enterprises, academia, and innovative start-ups worldwide within industries such as gaming, biotech , defense, healthcare, CPG, retail, financial services, among others.Starting Price: $15 -
28
QFlow.ai
QFlow.ai
The machine learning platform that unifies data, orchestrates intelligent behavior across revenue-generating teams, and delivers out-of-the-box attribution & actionable analytics. QFlow.ai processes the gigabytes of data that your Salesforce.com instance is collecting in its activity table. We normalize, trend, and analyze sales effort to help you generate more opportunities and win more deals. QFlow.ai uses data engineering to break down outbound activity reporting based on a crucial factor: whether or not they were productive. It also automatically surfaces critical metrics like average days from first activity to opp creation and average days from opp creation to close. Sales Effort data can be filtered by team or by an individual to understand sales activity, and productivity trends over time.Starting Price: $699 per month -
29
TensorStax
TensorStax
TensorStax is an AI-powered platform that automates data engineering tasks, enabling businesses to efficiently manage data pipelines, database migrations, ETL/ELT processes, and data ingestion within their cloud infrastructure. Its autonomous agents integrate seamlessly with existing tools like Airflow and dbt, facilitating end-to-end pipeline development and proactive issue detection to minimize downtime. Deployed within a company's Virtual Private Cloud (VPC), TensorStax ensures data security and privacy. By automating complex data workflows, it allows teams to focus on strategic analysis and decision-making. -
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Onum
Onum
Onum is a real-time data intelligence platform that empowers security and IT teams to derive actionable insights from data in-stream, facilitating rapid decision-making and operational efficiency. By processing data at the source, Onum enables decisions in milliseconds, not minutes, simplifying complex workflows and reducing costs. It offers data reduction capabilities, intelligently filtering and reducing data at the source to ensure only valuable information reaches analytics platforms, thereby minimizing storage requirements and associated costs. It also provides data enrichment features, transforming raw data into actionable intelligence by adding context and correlations in real time. Onum simplifies data pipeline management through efficient data routing, ensuring the right data is delivered to the appropriate destinations instantly, supporting various sources and destinations. -
31
UnionML
Union
Creating ML apps should be simple and frictionless. UnionML is an open-source Python framework built on top of Flyte™, unifying the complex ecosystem of ML tools into a single interface. Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. Using industry-standard machine learning methods, implement endpoints for fetching data, training models, serving predictions (and much more) to write a complete ML stack in one place. Data science, ML engineering, and MLOps practitioners can all gather around UnionML apps as a way of defining a single source of truth about your ML system’s behavior. -
32
witboost
Agile Lab
witboost is a modular, scalable, fast, efficient data management system for your company to truly become data driven, reduce time-to-market, it expenditures and overheads. witboost comprises a series of modules. These are building blocks that can work as standalone solutions to address and solve a single need or problem, or they can be combined to create the perfect data management ecosystem for your company. Each module improves a specific data engineering function and they can be combined to create the perfect solution to answer your specific needs, guaranteeing a blazingly fact and smooth implementation, thus dramatically reducing time-to-market, time-to-value and consequently the TCO of your data engineering infrastructure. Smart Cities need digital twins to predict needs and avoid unforeseen problems, gathering data from thousands of sources and managing ever more complex telematics. -
33
Gathr.ai
Gathr.ai
Gathr is a Data+AI fabric, helping enterprises rapidly deliver production-ready data and AI products. Data+AI fabric enables teams to effortlessly acquire, process, and harness data, leverage AI services to generate intelligence, and build consumer applications— all with unparalleled speed, scale, and confidence. Gathr’s self-service, AI-assisted, and collaborative approach enables data and AI leaders to achieve massive productivity gains by empowering their existing teams to deliver more valuable work in less time. With complete ownership and control over data and AI, flexibility and agility to experiment and innovate on an ongoing basis, and proven reliable performance at real-world scale, Gathr allows them to confidently accelerate POVs to production. Additionally, Gathr supports both cloud and air-gapped deployments, making it the ideal choice for diverse enterprise needs. Gathr, recognized by leading analysts like Gartner and Forrester, is a go-to-partner for Fortune 500Starting Price: $0.25/credit -
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Decodable
Decodable
No more low level code and stitching together complex systems. Build and deploy pipelines in minutes with SQL. A data engineering service that makes it easy for developers and data engineers to build and deploy real-time data pipelines for data-driven applications. Pre-built connectors for messaging systems, storage systems, and database engines make it easy to connect and discover available data. For each connection you make, you get a stream to or from the system. With Decodable you can build your pipelines with SQL. Pipelines use streams to send data to, or receive data from, your connections. You can also use streams to connect pipelines together to handle the most complex processing tasks. Observe your pipelines to ensure data keeps flowing. Create curated streams for other teams. Define retention policies on streams to avoid data loss during external system failures. Real-time health and performance metrics let you know everything’s working.Starting Price: $0.20 per task per hour -
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Key Ward
Key Ward
Extract, transform, manage, & process CAD, FE, CFD, and test data effortlessly. Create automatic data pipelines for machine learning, ROM, & 3D deep learning. Removing data science barriers without coding. Key Ward's platform is the first end-to-end engineering no-code solution that redefines how engineers interact with their data, experimental & CAx. Through leveraging engineering data intelligence, our software enables engineers to easily handle their multi-source data, extract direct value with our built-in advanced analytics tools, and custom-build their machine and deep learning models, all under one platform, all with a few clicks. Automatically centralize, update, extract, sort, clean, and prepare your multi-source data for analysis, machine learning, and/or deep learning. Use our advanced analytics tools on your experimental & simulation data to correlate, find dependencies, and identify patterns.Starting Price: €9,000 per year -
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The Autonomous Data Engine
Infoworks
There is a consistent “buzz” today about how leading companies are harnessing big data for competitive advantage. Your organization is striving to become one of those market-leading companies. However, the reality is that over 80% of big data projects fail to deploy to production because project implementation is a complex, resource-intensive effort that takes months or even years. The technology is complicated, and the people who have the necessary skills are either extremely expensive or impossible to find. Automates the complete data workflow from source to consumption. Automates migration of data and workloads from legacy Data Warehouse systems to big data platforms. Automates orchestration and management of complex data pipelines in production. Alternative approaches such as stitching together multiple point solutions or custom development are expensive, inflexible, time-consuming and require specialized skills to assemble and maintain. -
37
Mage
Mage
Mage is a tool that transforms your data into predictions. Build, train, and deploy predictive models in minutes. No AI experience required. Increase user engagement by ranking content on your user’s home feed. Increase conversion by showing the most relevant products for a user to buy. Increase retention by predicting which users will stop using your app. Increase conversion by matching users in a marketplace. Data is the most important part in building AI. Mage will guide you through this process with suggestions on how to improve your data, making you an AI expert. AI and its predictions are difficult to understand. Mage explains every metric in-depth, teaching you how your AI model thinks. Get real-time predictions with a few lines of code. Mage makes it easy for you to integrate your AI model in any application.Starting Price: Free -
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Lumada IIoT
Hitachi
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. -
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Fosfor Decision Cloud
Fosfor
Everything you need to make better business decisions. The Fosfor Decision Cloud unifies the modern data ecosystem to deliver the long-sought promise of AI: enhanced business outcomes. The Fosfor Decision Cloud unifies the components of your data stack into a modern decision stack, built to amplify business outcomes. Fosfor works seamlessly with its partners to create the modern decision stack, which delivers unprecedented value from your data investments. -
40
OHIF Viewer
OHIF
The Open Health Imaging Foundation (OHIF) Viewer is an open source, web-based medical imaging platform designed to serve as a foundational framework for developing complex imaging applications. It is optimized for the rapid loading of extensive radiology studies by pre-fetching metadata and streaming imaging pixel data as required. It utilizes Cornerstone3D for efficient decoding, rendering, and annotation of medical images. Out-of-the-box compatibility with DICOMWeb-compliant image archives is provided, alongside a data source API for integration with archives using proprietary API formats. OHIF's plugin architecture facilitates the creation of task-specific workflow modes that can leverage existing core functionalities. The user interface, built with React.js and Tailwind CSS, is both aesthetically pleasing and designed for extensibility, with UI components available in a reusable component library.Starting Price: Free -
41
Amazon MWAA
Amazon
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.Starting Price: $0.49 per hour -
42
Modelbit
Modelbit
Don't change your day-to-day, works with Jupyter Notebooks and any other Python environment. Simply call modelbi.deploy to deploy your model, and let Modelbit carry it — and all its dependencies — to production. ML models deployed with Modelbit can be called directly from your warehouse as easily as calling a SQL function. They can also be called as a REST endpoint directly from your product. Modelbit is backed by your git repo. GitHub, GitLab, or home grown. Code review. CI/CD pipelines. PRs and merge requests. Bring your whole git workflow to your Python ML models. Modelbit integrates seamlessly with Hex, DeepNote, Noteable and more. Take your model straight from your favorite cloud notebook into production. Sick of VPC configurations and IAM roles? Seamlessly redeploy your SageMaker models to Modelbit. Immediately reap the benefits of Modelbit's platform with the models you've already built. -
43
Bodo.ai
Bodo.ai
Bodo’s powerful compute engine and parallel computing approach provides efficient execution and effective scalability even for 10,000+ cores and PBs of data. Bodo enables faster development and easier maintenance for data science, data engineering and ML workloads with standard Python APIs like Pandas. Avoid frequent failures with bare-metal native code execution and catch errors before they appear in production with end-to-end compilation. Experiment faster with large datasets on your laptop with the simplicity that only Python can provide. Write production-ready code without the hassle of refactoring for scaling on large infrastructure! -
44
IBM watsonx.data integration is a data integration platform designed to help organizations transform raw data into AI-ready data at scale. The platform enables data teams to build, manage, and optimize data pipelines across multiple environments, including on-premises systems and hybrid or multi-cloud infrastructures. With a unified control plane, watsonx.data integration supports multiple integration styles such as batch processing, real-time streaming, and data replication within a single solution. The platform also offers no-code, low-code, and pro-code development options, allowing both technical and non-technical users to design and manage data pipelines efficiently. By simplifying data integration workflows and reducing reliance on multiple tools, watsonx.data integration helps organizations deliver reliable data for analytics and AI applications.
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45
DatErica
DatErica
DatErica: Revolutionizing Data Processing DatErica is a cutting-edge data processing platform designed to automate and streamline data operations. Leveraging a robust technology stack including Node.js and microservice architecture, it provides scalable and flexible solutions for complex data needs. The platform offers advanced ETL capabilities, seamless data integration from various sources, and secure data warehousing. DatErica's AI-powered tools enable sophisticated data transformation and validation, ensuring accuracy and consistency. With real-time analytics, customizable dashboards, and automated reporting, users gain valuable insights for informed decision-making. The user-friendly interface simplifies workflow management, while real-time monitoring and alerts enhance operational efficiency. DatErica is ideal for data engineers, analysts, IT teams, and businesses seeking to optimize their data processes and drive growth.Starting Price: 9 -
46
RTE Runner
Cybersoft North America
It is the artificial intelligence solution to analyze complex data, empower decision making and transform human and industrial productivity. It is the automated machine solution that has the potential to reduce the burden on already overwhelmed teams by automating the main bottlenecks in the data science process. It breaks data silos with the intuitive creation of data pipelines that feed live data into deployed models and then dynamically creates model execution pipelines to obtain real-time predictions on incoming data. It monitors the health of deployed models based on the confidence of predictions to inform model maintenance. -
47
Pathway
Pathway
Pathway is a Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG. Pathway comes with an easy-to-use Python API, allowing you to seamlessly integrate your favorite Python ML libraries. Pathway code is versatile and robust: you can use it in both development and production environments, handling both batch and streaming data effectively. The same code can be used for local development, CI/CD tests, running batch jobs, handling stream replays, and processing data streams. Pathway is powered by a scalable Rust engine based on Differential Dataflow and performs incremental computation. Your Pathway code, despite being written in Python, is run by the Rust engine, enabling multithreading, multiprocessing, and distributed computations. All the pipeline is kept in memory and can be easily deployed with Docker and Kubernetes. -
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Dremio
Dremio
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. -
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Apache PredictionIO
Apache
Apache PredictionIO® is an open-source machine learning server built on top of a state-of-the-art open-source stack for developers and data scientists to create predictive engines for any machine learning task. It lets you quickly build and deploy an engine as a web service on production with customizable templates. Respond to dynamic queries in real-time once deployed as a web service, evaluate and tune multiple engine variants systematically, and unify data from multiple platforms in batch or in real-time for comprehensive predictive analytics. Speed up machine learning modeling with systematic processes and pre-built evaluation measures, support machine learning and data processing libraries such as Spark MLLib and OpenNLP. Implement your own machine learning models and seamlessly incorporate them into your engine. Simplify data infrastructure management. Apache PredictionIO® can be installed as a full machine learning stack, bundled with Apache Spark, MLlib, HBase, Akka HTTP, etc.Starting Price: Free -
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Talend Pipeline Designer is a web-based self-service application that takes raw data and makes it analytics-ready. Compose reusable pipelines to extract, improve, and transform data from almost any source, then pass it to your choice of data warehouse destinations, where it can serve as the basis for the dashboards that power your business insights. Build and deploy data pipelines in less time. Design and preview, in batch or streaming, directly in your web browser with an easy, visual UI. Scale with native support for the latest hybrid and multi-cloud technologies, and improve productivity with real-time development and debugging. Live preview lets you instantly and visually diagnose issues with your data. Make better decisions faster with dataset documentation, quality proofing, and promotion. Transform data and improve data quality with built-in functions applied across batch or streaming pipelines, turning data health into an effortless, automated discipline.
