Alternatives to Lightbend
Compare Lightbend alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Lightbend in 2026. Compare features, ratings, user reviews, pricing, and more from Lightbend competitors and alternatives in order to make an informed decision for your business.
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Google Cloud Platform
Google
Google Cloud is a cloud-based service that allows you to create anything from simple websites to complex applications for businesses of all sizes. New customers get $300 in free credits to run, test, and deploy workloads. All customers can use 25+ products for free, up to monthly usage limits. Use Google's core infrastructure, data analytics & machine learning. Secure and fully featured for all enterprises. Tap into big data to find answers faster and build better products. Grow from prototype to production to planet-scale, without having to think about capacity, reliability or performance. From virtual machines with proven price/performance advantages to a fully managed app development platform. Scalable, resilient, high performance object storage and databases for your applications. State-of-the-art software-defined networking products on Google’s private fiber network. Fully managed data warehousing, batch and stream processing, data exploration, Hadoop/Spark, and messaging. -
2
Minitab Connect
Minitab
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. -
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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. -
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Spring Cloud Data Flow
Spring
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. -
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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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HPE Ezmeral
Hewlett Packard Enterprise
Run, manage, control and secure the apps, data and IT that run your business, from edge to cloud. HPE Ezmeral advances digital transformation initiatives by shifting time and resources from IT operations to innovations. Modernize your apps. Simplify your Ops. And harness data to go from insights to impact. Accelerate time-to-value by deploying Kubernetes at scale with integrated persistent data storage for app modernization on bare metal or VMs, in your data center, on any cloud or at the edge. Harness data and get insights faster by operationalizing the end-to-end process to build data pipelines. Bring DevOps agility to the machine learning lifecycle, and deliver a unified data fabric. Boost efficiency and agility in IT Ops with automation and advanced artificial intelligence. And provide security and control to eliminate risk and reduce costs. HPE Ezmeral Container Platform provides an enterprise-grade platform to deploy Kubernetes at scale for a wide range of use cases. -
7
Akka
Akka
Akka is a toolkit for building highly concurrent, distributed, and resilient message-driven applications for Java and Scala. Akka Insights is intelligent monitoring and observability purpose-built for Akka. Actors and Streams let you build systems that scale up, using the resources of a server more efficiently, and out, using multiple servers. Building on the principles of The Reactive Manifesto Akka allows you to write systems that self-heal and stay responsive in the face of failures. Distributed systems without single points of failure. Load balancing and adaptive routing across nodes. Event Sourcing and CQRS with Cluster Sharding. Distributed Data for eventual consistency using CRDTs. Asynchronous non-blocking stream processing with backpressure. Fully async and streaming HTTP server and client provides a great platform for building microservices. Streaming integrations with Alpakka. -
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Upsolver
Upsolver
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. -
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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.
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10
IBM StreamSets
IBM
IBM® StreamSets enables users to create and manage smart streaming data pipelines through an intuitive graphical interface, facilitating seamless data integration across hybrid and multicloud environments. This is why leading global companies rely on IBM StreamSets to support millions of data pipelines for modern analytics, intelligent applications and hybrid integration. Decrease data staleness and enable real-time data at scale—handling millions of records of data, across thousands of pipelines within seconds. Insulate data pipelines from change and unexpected shifts with drag-and-drop, prebuilt processors designed to automatically identify and adapt to data drift. Create streaming pipelines to ingest structured, semistructured or unstructured data and deliver it to a wide range of destinations.Starting Price: $1000 per month -
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StreamScape
StreamScape
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. -
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Orchestra
Orchestra
Orchestra is a Unified Control Plane for Data and AI Operations, designed to help data teams build, deploy, and monitor workflows with ease. It offers a declarative framework that combines code and GUI, allowing users to implement workflows 10x faster and reduce maintenance time by 50%. With real-time metadata aggregation, Orchestra provides full-stack data observability, enabling proactive alerting and rapid recovery from pipeline failures. It integrates seamlessly with tools like dbt Core, dbt Cloud, Coalesce, Airbyte, Fivetran, Snowflake, BigQuery, Databricks, and more, ensuring compatibility with existing data stacks. Orchestra's modular architecture supports AWS, Azure, and GCP, making it a versatile solution for enterprises and scale-ups aiming to streamline their data operations and build trust in their AI initiatives. -
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Pandio
Pandio
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.Starting Price: $1.40 per hour -
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Data Taps
Data Taps
Build your data pipelines like Lego blocks with Data Taps. Add new metrics layers, zoom in, and investigate with real-time streaming SQL. Build with others, share and consume data, globally. Refine and update without hassle. Use multiple models/schemas during schema evolution. Built to scale with AWS Lambda and S3. -
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Ingestro
Ingestro
Ingestro is an enterprise-grade, AI-powered data import solution designed to help software companies clean, validate, and onboard customer data faster. It supports uploads from a wide variety of formats—including CSV, Excel, XML, JSON, and even PDFs—while automatically mapping, cleaning, and restructuring the data to match each company’s schema. With its Data Importer SDK and Data Pipelines, Ingestro enables teams to offer a seamless self-serve import experience without building in-house tools. The platform improves scalability by automating recurring data onboarding tasks, reducing dependency on developers, and accelerating customer time-to-value. Companies rely on Ingestro to process billions of records securely thanks to features like ISO 27001 certification, GDPR compliance, and optional self-hosting. By transforming tedious data imports into smooth, AI-enhanced workflows, Ingestro helps product, engineering, and customer success teams reclaim valuable time. -
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Azure Event Hubs
Microsoft
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.Starting Price: $0.03 per hour -
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Tencent Kubernetes Engine
Tencent
TKE is fully compatible with the entire range of Kubernetes capabilities and has been adapted to Tencent Cloud's fundamental IaaS capabilities such as CVM and CBS. In addition, Tencent Cloud’s Kubernetes-based cloud products such as CBS and CLB support one-click deployment to container clusters for a variety of open source applications, greatly improving deployment efficiency. Thanks to TKE, you can simplify the management of large-scale clusters and management and OPS of distributed applications without having to use cluster management software or design fault-tolerant cluster architecture. Simply launch TKE and specify the tasks you want to run, and then TKE will take care of all of the cluster management tasks, allowing you to focus on developing Dockerized applications. -
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Nextflow
Seqera Labs
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.Starting Price: Free -
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StreamNative
StreamNative
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.Starting Price: $1,000 per month -
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Hevo
Hevo Data
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.Starting Price: $249/month -
21
Arcion
Arcion Labs
Deploy production-ready change data capture pipelines for high-volume, real-time data replication - without a single line of code. Supercharged Change Data Capture. Enjoy automatic schema conversion, end-to-end replication, flexible deployment, and more with Arcion’s distributed Change Data Capture (CDC). Leverage Arcion’s zero data loss architecture for guaranteed end-to-end data consistency, built-in checkpointing, and more without any custom code. Leave scalability and performance concerns behind with a highly-distributed, highly parallel architecture supporting 10x faster data replication. Reduce DevOps overhead with Arcion Cloud, the only fully-managed CDC offering. Enjoy autoscaling, built-in high availability, monitoring console, and more. Simplify & standardize data pipelines architecture, and zero downtime workload migration from on-prem to cloud.Starting Price: $2,894.76 per month -
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Datazoom
Datazoom
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. -
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VMware Tanzu Kubernetes Grid
Broadcom
Power your modern applications with VMware Tanzu Kubernetes Grid. Run the same K8s across data center, public cloud and edge for a consistent, secure experience for all development teams. Keep your workloads properly isolated and secure. Get a complete, easy-to-upgrade Kubernetes runtime with preintegrated and validated components. Deploy and scale all clusters without downtime. Apply security fixes fast. Run your containerized applications on a certified Kubernetes distribution, bolstered by the global Kubernetes community. Use your existing data center tools and workflows to give developers secure, self-serve access to conformant Kubernetes clusters in your VMware private cloud, and extend the same consistent Kubernetes runtime across your public cloud and edge environments. Simplify operations of large-scale, multicluster Kubernetes environments, and keep your workloads properly isolated. Automate lifecycle management to reduce your risk and shift your focus to more strategic work. -
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Gravity Data
Gravity
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. -
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AWS Data Pipeline
Amazon
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.Starting Price: $1 per month -
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Qlik Compose
Qlik
Qlik 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 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. -
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BigBI
BigBI
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 -
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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. -
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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 -
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SUSE Rancher Prime
SUSE
SUSE Rancher Prime addresses the needs of DevOps teams deploying applications with Kubernetes and IT operations delivering enterprise-critical services. SUSE Rancher Prime supports any CNCF-certified Kubernetes distribution. For on-premises workloads, we offer the RKE. We support all the public cloud distributions, including EKS, AKS, and GKE. At the edge, we offer K3s. SUSE Rancher Prime provides simple, consistent cluster operations, including provisioning, version management, visibility and diagnostics, monitoring and alerting, and centralized audit. SUSE Rancher Prime lets you automate processes and applies a consistent set of user access and security policies for all your clusters, no matter where they’re running. SUSE Rancher Prime provides a rich catalogue of services for building, deploying, and scaling containerized applications, including app packaging, CI/CD, logging, monitoring, and service mesh. -
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Kubevious
Kubevious
Kubevious helps you avoid breaking apps and producing bad or conflicting configurations. It brings operational safety to your apps and makes your teams efficient and successful, without interfering with existing DevOps processes. Kubevious helps Kubernetes operators to quickly identify configuration specifics, inconsistencies, compliance, and best practices violations. Kubevious application-centric UI is unique. By correlating configurations, it allows operators to be efficient and get the most out of Kubernetes. Kubevious validates and enforces cloud-native best practices. Achieve ultimate safety across all domains: application configuration, state, RBAC, storage, networking, service mesh, and more. Kubernetes operators love the user friendly and intuitive interface provided by Kubevious. Kubevious is equipped with rules engine which was purposely build to enforce application and cloud native best practices in Kubernetes. -
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Trifacta
Trifacta
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. -
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Apprenda
Apprenda
Apprenda Cloud Platform empowers enterprise IT to create a Kubernetes-enabled shared service on the infrastructures of their choice and offer it to developers across business units. ACP supports your entire custom application portfolio. Rapidly build, deploy, run, and manage cloud-native, microservices, and container-based .NET and Java applications or modernize traditional workloads. ACP gives your developers self-service access to the tools they need to rapidly build applications, while IT operators can very easily orchestrate the environments and workflows. Enterprise IT becomes a true service provider. ACP is a single platform spanning your multiple data- centers and clouds. Run ACP on-premise or consume it as a managed service on the public cloud; both with the assurance of complete infrastructure independence. ACP enables policy-driven control over all of your application workloads' infrastructure utilization and DevOps processes. -
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Yandex Data Proc
Yandex
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.Starting Price: $0.19 per hour -
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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 -
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Deploy and orchestrate applications on a managed Kubernetes platform with centralized, SaaS-based management of distributed applications with a single pane of glass and rich observability. Simplify by managing deployments as one across on-prem, cloud, and edge locations. Achieve effortless management and scaling of applications across multiple k8s clusters (customer sites or F5 Distributed Cloud Regional Edge) with a single Kubernetes compatible API, unlocking the ease of multi-cluster management. Deploy, deliver, and secure applications to all locations as one ”virtual” location. Deploy, secure, and operate distributed applications with uniform production grade Kubernetes no matter the location, from private and public cloud to edge locations. Secure K8s Gateway with zero trust security all the way to the cluster with ingress services with WAAP, service policies management, network, and application firewall.
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37
Hazelcast
Hazelcast
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. -
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Cloud Foundry
Cloud Foundry
Cloud Foundry makes it faster and easier to build, test, deploy and scale applications, providing a choice of clouds, developer frameworks, and application services. It is an open source project and is available through a variety of private cloud distributions and public cloud instances. Cloud Foundry has a container-based architecture that runs apps in any programming language. Deploy apps to CF using your existing tools and with zero modification to the code. Instantiate, deploy, and manage high-availability Kubernetes clusters with CF BOSH on any cloud. By decoupling applications from infrastructure, you can make individual decisions about where to host workloads – on premise, in public clouds, or in managed infrastructures – and move those workloads as necessary in minutes, with no changes to the app. -
39
AppFactor
AppFactor
AppFactor significantly reduces the cost and labor that would otherwise be required for a manual application modernization project. Post modernization, our platform empowers teams to deploy, operate, and maintain existing applications more efficiently and cost-effectively, Increase engineering velocity, level-up your business-critical applications, streamline innovation, and gain a competitive edge. Quickly transform legacy physical and virtual server-based apps into cloud-native form to kickstart iterative modernization of architecture, deployment, and improvements. Intelligently persist runtime and process-to-process relationships from multiple server hosts into cloud-native architectures. Accelerate and induct legacy apps into CI/CD pipelines. Remove older physical and virtual infrastructure along with having to maintain operating systems. Simplify cloud migration by modernizing as you go to more mature cloud services such as Kubernetes platforms or PaaS. -
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Apache Kafka
The Apache Software Foundation
Apache Kafka® is an open-source, distributed streaming platform. Scale production clusters up to a thousand brokers, trillions of messages per day, petabytes of data, hundreds of thousands of partitions. Elastically expand and contract storage and processing. Stretch clusters efficiently over availability zones or connect separate clusters across geographic regions. Process streams of events with joins, aggregations, filters, transformations, and more, using event-time and exactly-once processing. Kafka’s out-of-the-box Connect interface integrates with hundreds of event sources and event sinks including Postgres, JMS, Elasticsearch, AWS S3, and more. Read, write, and process streams of events in a vast array of programming languages. -
41
Leonovus Vault
Leonovus
Our unique enterprise data management solution decouples your data from the infrastructure in which it is stored. Vault applies data-centric security controls to ensure that your data remains protected wherever it resides. Bulk and archive data are ‘shredded’ into discrete, encrypted objects that are distributed across hybrid and multi-cloud storage. Vault allows you to embrace public cloud storage securely, efficiently and with the flexibility to evolve with the dynamic cloud storage market. -
42
Alooma
Google
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. -
43
Tencent Container Registry
Tencent
Tencent Container Registry (TCR) offers secure, dedicated, and high-performance container image hosting and distribution service. You can create dedicated instances in multiple regions across the globe and pull container images from the nearest region to reduce pulling time and bandwidth costs. To guarantee data security, TCR features granular permission management and access control. It also supports P2P accelerated distribution to break through the performance bottleneck due to concurrent pulling of large images by large-scale clusters, helping you quickly expand and update businesses. You can customize image synchronization rules and triggers, and use TCR flexibly with your existing CI/CD workflow to quickly implement container DevOps. TCR instance adopts containerized deployment. You can dynamically adjust the service capability based on actual usage to manage sudden surges in business traffic. -
44
IBM Storage for Red Hat OpenShift unifies traditional and container storage, enabling easier deployment of enterprise-class scale-out microservices architectures. Validated with Red Hat OpenShift, Kubernetes and IBM Cloud Pak. Delivering simplified deployment and management for an integrated experience. Enterprise data protection, automated scheduling, and data reuse support for Red Hat OpenShift and Kubernetes environments. Block, file and object data resources. Quickly deploy what you need when you need it. IBM Storage for Red Hat OpenShift provides the infrastructure foundation and storage orchestration necessary for building a robust, agile, on-premises hybrid cloud environment. IBM supports CSI for its block and file storage families to improve container utilization in Kubernetes environments.
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45
Joyent Triton
Joyent
Single Tenant Public Cloud with all the security, savings and control of private cloud. Fully Managed by Joyent. Single Tenant Security, Full Operations control over your Private Cloud with Installation, Onboarding and Support provided by Joyent. Open Source or Commercial support for on-premises, user managed private cloud. Built to deliver VMs, containers and bare metal. Built to support exabyte-scale workloads. Joyent engineers provide 360 degree support for modern application architectures, including microservices, apis, development frameworks and container-native devops tooling. Hybrid, Modern and Open, Triton is engineered to run the world’s largest cloud native applications. -
46
Actifio
Google
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. -
47
D2iQ
D2iQ
D2iQ Enterprise Kubernetes Platform (DKP) Run Kubernetes Workloads at Scale DKP includes everything you need to ease Kubernetes adoption, expand Kubernetes use, and enable advanced workloads across any infrastructure, whether on-prem, on the cloud, in air-gapped environments, or at the edge. Built to Solve the Toughest Enterprise Kubernetes Challenges Created to accelerate the journey to production at scale, DKP provides a single, centralized point of control to build, run, and manage applications across any infrastructure. Enable Day 2 Readiness Out-of-the-Box Without Lock-In DKP takes care of the heavy lifting by providing a comprehensive, enterprise-grade Kubernetes distribution and a full stack of CNCF-certified Day 2 platform applications that are integrated, automated, and tested at scale for an out-of-the-box, production-ready experience. -
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BDB Platform
Big Data BizViz
BDB is a modern data analytics and BI platform which can skillfully dive deep into your data to provide actionable insights. It is deployable on the cloud as well as on-premise. Our exclusive microservices based architecture has the elements of Data Preparation, Predictive, Pipeline and Dashboard designer to provide customized solutions and scalable analytics to different industries. BDB’s strong NLP based search enables the user to unleash the power of data on desktop, tablets and mobile as well. BDB has various ingrained data connectors, and it can connect to multiple commonly used data sources, applications, third party API’s, IoT, social media, etc. in real-time. It lets you connect to RDBMS, Big data, FTP/ SFTP Server, flat files, web services, etc. and manage structured, semi-structured as well as unstructured data. Start your journey to advanced analytics today. -
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Managed Service for Apache Airflow is a fully managed workflow orchestration platform from Google Cloud built on the open-source Apache Airflow project. It allows users to author, schedule, and monitor data pipelines using Python-based workflows known as DAGs. The platform eliminates the need to manage infrastructure, enabling teams to focus on building and running pipelines. It integrates seamlessly with Google Cloud services such as BigQuery, Dataflow, and Managed Service for Apache Spark. It also supports hybrid and multi-cloud environments, allowing workflows to span across different systems. Users benefit from built-in monitoring, logging, and troubleshooting tools for reliability. The service is designed to simplify complex data workflows, including ETL, MLOps, and automation tasks. Overall, it provides a scalable and flexible solution for orchestrating modern data pipelines.Starting Price: $0.074 per vCPU hour
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Pantomath
Pantomath
Organizations continuously strive to be more data-driven, building dashboards, analytics, and data pipelines across the modern data stack. Unfortunately, most organizations struggle with data reliability issues leading to poor business decisions and lack of trust in data as an organization, directly impacting their bottom line. Resolving complex data issues is a manual and time-consuming process involving multiple teams all relying on tribal knowledge to manually reverse engineer complex data pipelines across different platforms to identify root-cause and understand the impact. Pantomath is a data pipeline observability and traceability platform for automating data operations. It continuously monitors datasets and jobs across the enterprise data ecosystem providing context to complex data pipelines by creating automated cross-platform technical pipeline lineage.