Alternatives to IBM StreamSets
Compare IBM StreamSets alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to IBM StreamSets in 2026. Compare features, ratings, user reviews, pricing, and more from IBM StreamSets competitors and alternatives in order to make an informed decision for your business.
-
1
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. -
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. -
3
Rivery
Rivery
Rivery’s SaaS ETL platform provides a fully-managed solution for data ingestion, transformation, orchestration, reverse ETL and more, with built-in support for your development and deployment lifecycles. Key Features: Data Workflow Templates: Extensive library of pre-built templates that enable teams to instantly create powerful data pipelines with the click of a button. Fully managed: No-code, auto-scalable, and hassle-free platform. Rivery takes care of the back end, allowing teams to spend time on priorities rather than maintenance. Multiple Environments: Construct and clone custom environments for specific teams or projects. Reverse ETL: Automatically send data from cloud warehouses to business applications, marketing clouds, CPD’s, and more.Starting Price: $0.75 Per Credit -
4
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. -
5
Striim
Striim
Data integration for your hybrid cloud. Modern, reliable data integration across your private and public cloud. All in real-time with change data capture and data streams. Built by the executive & technical team from GoldenGate Software, Striim brings decades of experience in mission-critical enterprise workloads. Striim scales out as a distributed platform in your environment or in the cloud. Scalability is fully configurable by your team. Striim is fully secure with HIPAA and GDPR compliance. Built ground up for modern enterprise workloads in the cloud or on-premise. Drag and drop to create data flows between your sources and targets. Process, enrich, and analyze your streaming data with real-time SQL queries. -
6
Apache Airflow
The Apache Software Foundation
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. -
7
SAS Event Stream Processing
SAS Institute
Streaming data from operations, transactions, sensors and IoT devices is valuable – when it's well-understood. Event stream processing from SAS includes streaming data quality and analytics – and a vast array of SAS and open source machine learning and high-frequency analytics for connecting, deciphering, cleansing and understanding streaming data – in one solution. No matter how fast your data moves, how much data you have, or how many data sources you’re pulling from, it’s all under your control via a single, intuitive interface. You can define patterns and address scenarios from all aspects of your business, giving you the power to stay agile and tackle issues as they arise. -
8
Precisely Connect
Precisely
Integrate data seamlessly from legacy systems into next-gen cloud and data platforms with one solution. Connect helps you take control of your data from mainframe to cloud. Integrate data through batch and real-time ingestion for advanced analytics, comprehensive machine learning and seamless data migration. Connect leverages the expertise Precisely has built over decades as a leader in mainframe sort and IBM i data availability and security to lead the industry in accessing and integrating complex data. Access to all your enterprise data for the most critical business projects is ensured by support for a wide range of sources and targets for all your ELT and CDC needs. -
9
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 -
10
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. -
11
Cloudera DataFlow
Cloudera
Cloudera DataFlow for the Public Cloud (CDF-PC) is a cloud-native universal data distribution service powered by Apache NiFi that lets developers connect to any data source anywhere with any structure, process it, and deliver to any destination. CDF-PC offers a flow-based low-code development paradigm that aligns best with how developers design, develop, and test data distribution pipelines. With over 400+ connectors and processors across the ecosystem of hybrid cloud services—including data lakes, lakehouses, cloud warehouses, and on-premises sources—CDF-PC provides indiscriminate data distribution. These data distribution flows can then be version-controlled into a catalog where operators can self-serve deployments to different runtimes. -
12
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. -
13
Informatica Data Engineering Streaming
Informatica
AI-powered Informatica Data Engineering Streaming enables data engineers to ingest, process, and analyze real-time streaming data for actionable insights. Advanced serverless deployment option with integrated metering dashboard cuts admin overhead. 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. Efficiently ingest databases, files, and streaming data for real-time data replication and streaming analytics. Find and inventory all data assets throughout your organization. Intelligently discover and prepare trusted data for advanced analytics and AI/ML projects. -
14
Confluent
Confluent
Infinite retention for Apache Kafka® with Confluent. Be infrastructure-enabled, not infrastructure-restricted Legacy technologies require you to choose between being real-time or highly-scalable. Event streaming enables you to innovate and win - by being both real-time and highly-scalable. Ever wonder how your rideshare app analyzes massive amounts of data from multiple sources to calculate real-time ETA? Ever wonder how your credit card company analyzes millions of credit card transactions across the globe and sends fraud notifications in real-time? The answer is event streaming. Move to microservices. Enable your hybrid strategy through a persistent bridge to cloud. Break down silos to demonstrate compliance. Gain real-time, persistent event transport. The list is endless. -
15
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.
-
16
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. -
17
Streaming service is a real-time, serverless, Apache Kafka-compatible event streaming platform for developers and data scientists. Streaming is tightly integrated with Oracle Cloud Infrastructure (OCI), Database, GoldenGate, and Integration Cloud. The service also provides out-of-the-box integrations for hundreds of third-party products across categories such as DevOps, databases, big data, and SaaS applications. Data engineers can easily set up and operate big data pipelines. Oracle handles all infrastructure and platform management for event streaming, including provisioning, scaling, and security patching. With the help of consumer groups, Streaming can provide state management for thousands of consumers. This helps developers easily build applications at scale.
-
18
DeltaStream
DeltaStream
DeltaStream is a unified serverless stream processing platform that integrates with streaming storage services. Think about it as the compute layer on top of your streaming storage. It provides functionalities of streaming analytics(Stream processing) and streaming databases along with additional features to provide a complete platform to manage, process, secure and share streaming data. DeltaStream provides a SQL based interface where you can easily create stream processing applications such as streaming pipelines, materialized views, microservices and many more. It has a pluggable processing engine and currently uses Apache Flink as its primary stream processing engine. DeltaStream is more than just a query processing layer on top of Kafka or Kinesis. It brings relational database concepts to the data streaming world, including namespacing and role based access control enabling you to securely access, process and share your streaming data regardless of where they are stored. -
19
Amazon MSK
Amazon
Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed service that makes it easy for you to build and run applications that use Apache Kafka to process streaming data. Apache Kafka is an open-source platform for building real-time streaming data pipelines and applications. With Amazon MSK, you can use native Apache Kafka APIs to populate data lakes, stream changes to and from databases, and power machine learning and analytics applications. Apache Kafka clusters are challenging to setup, scale, and manage in production. When you run Apache Kafka on your own, you need to provision servers, configure Apache Kafka manually, replace servers when they fail, orchestrate server patches and upgrades, architect the cluster for high availability, ensure data is durably stored and secured, setup monitoring and alarms, and carefully plan scaling events to support load changes.Starting Price: $0.0543 per hour -
20
Lenses
Lenses.io
Enable everyone to discover and observe streaming data. Sharing, documenting and cataloging your data can increase productivity by up to 95%. Then from data, build apps for production use cases. Apply a data-centric security model to cover all the gaps of open source technology, and address data privacy. Provide secure and low-code data pipeline capabilities. Eliminate all darkness and offer unparalleled observability in data and apps. Unify your data mesh and data technologies and be confident with open source in production. Lenses is the highest rated product for real-time stream analytics according to independent third party reviews. With feedback from our community and thousands of engineering hours invested, we've built features that ensure you can focus on what drives value from your real time data. Deploy and run SQL-based real time applications over any Kafka Connect or Kubernetes infrastructure including AWS EKS.Starting Price: $49 per month -
21
Datavolo
Datavolo
Capture all your unstructured data for all your LLM needs. Datavolo replaces single-use, point-to-point code with fast, flexible, reusable pipelines, freeing you to focus on what matters most, doing incredible work. Datavolo is the dataflow infrastructure that gives you a competitive edge. Get fast, unencumbered access to all of your data, including the unstructured files that LLMs rely on, and power up your generative AI. Get pipelines that grow with you, in minutes, not days, without custom coding. Instantly configure from any source to any destination at any time. Trust your data because lineage is built into every pipeline. Make single-use pipelines and expensive configurations a thing of the past. Harness your unstructured data and unleash AI innovation with Datavolo, powered by Apache NiFi and built specifically for unstructured data. Our founders have spent a lifetime helping organizations make the most of their data.Starting Price: $36,000 per year -
22
Amazon Kinesis
Amazon
Easily collect, process, and analyze video and data streams in real time. Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost-effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit the requirements of your application. With Amazon Kinesis, you can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications. Amazon Kinesis enables you to process and analyze data as it arrives and respond instantly instead of having to wait until all your data is collected before the processing can begin. Amazon Kinesis enables you to ingest, buffer, and process streaming data in real-time, so you can derive insights in seconds or minutes instead of hours or days. -
23
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 -
24
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 -
25
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 -
26
WarpStream
WarpStream
WarpStream is an Apache Kafka-compatible data streaming platform built directly on top of object storage, with no inter-AZ networking costs, no disks to manage, and infinitely scalable, all within your VPC. WarpStream is deployed as a stateless and auto-scaling agent binary in your VPC with no local disks to manage. Agents stream data directly to and from object storage with no buffering on local disks and no data tiering. Create new “virtual clusters” in our control plane instantly. Support different environments, teams, or projects without managing any dedicated infrastructure. WarpStream is protocol compatible with Apache Kafka, so you can keep using all your favorite tools and software. No need to rewrite your application or use a proprietary SDK. Just change the URL in your favorite Kafka client library and start streaming. Never again have to choose between reliability and your budget.Starting Price: $2,987 per month -
27
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. -
28
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. -
29
Axual
Axual
Axual is Kafka-as-a-Service for DevOps teams. Empower your team to unlock insights and drive decisions with our intuitive Kafka platform. Axual offers the ultimate solution for enterprises looking to seamlessly integrate data streaming into their core IT infrastructure. Our all-in-one Kafka platform is designed to eliminate the need for extensive technical knowledge or skills, and provides a ready-made solution that delivers all the benefits of event streaming without the hassle. The Axual Platform is a all-in-one solution, designed to help you simplify and enhance the deployment, management, and utilization of real-time data streaming with Apache Kafka. By providing an array of features that cater to the diverse needs of modern enterprises, the Axual Platform enables organizations to harness the full potential of data streaming while minimizing complexity and operational overhead. -
30
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 -
31
Google Cloud Data Fusion
Google
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. -
32
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 -
33
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. -
34
Arroyo
Arroyo
Scale from zero to millions of events per second. Arroyo ships as a single, compact binary. Run locally on MacOS or Linux for development, and deploy to production with Docker or Kubernetes. Arroyo is a new kind of stream processing engine, built from the ground up to make real-time easier than batch. Arroyo was designed from the start so that anyone with SQL experience can build reliable, efficient, and correct streaming pipelines. Data scientists and engineers can build end-to-end real-time applications, models, and dashboards, without a separate team of streaming experts. Transform, filter, aggregate, and join data streams by writing SQL, with sub-second results. Your streaming pipelines shouldn't page someone just because Kubernetes decided to reschedule your pods. Arroyo is built to run in modern, elastic cloud environments, from simple container runtimes like Fargate to large, distributed deployments on the Kubernetes logo Kubernetes. -
35
Astra Streaming
DataStax
Responsive applications keep users engaged and developers inspired. Rise to meet these ever-increasing expectations with the DataStax Astra Streaming service platform. DataStax Astra Streaming is a cloud-native messaging and event streaming platform powered by Apache Pulsar. Astra Streaming allows you to build streaming applications on top of an elastically scalable, multi-cloud messaging and event streaming platform. Astra Streaming is powered by Apache Pulsar, the next-generation event streaming platform which provides a unified solution for streaming, queuing, pub/sub, and stream processing. Astra Streaming is a natural complement to Astra DB. Using Astra Streaming, existing Astra DB users can easily build real-time data pipelines into and out of their Astra DB instances. With Astra Streaming, avoid vendor lock-in and deploy on any of the major public clouds (AWS, GCP, Azure) compatible with open-source Apache Pulsar. -
36
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. -
37
PubSub+ Platform
Solace
Solace PubSub+ Platform helps enterprises design, deploy and manage event-driven systems across hybrid and multi-cloud and IoT environments so they can be more event-driven and operate in real-time. The PubSub+ Platform includes the powerful PubSub+ Event Brokers, event management capabilities with PubSub+ Event Portal, as well as monitoring and integration capabilities all available via a single cloud console. PubSub+ allows easy creation of an event mesh, an interconnected network of event brokers, allowing for seamless and dynamic data movement across highly distributed network environments. PubSub+ Event Brokers can be deployed as fully managed cloud services, self-managed software in private cloud or on-premises environments, or as turnkey hardware appliances for unparalleled performance and low TCO. PubSub+ Event Portal is a complimentary toolset for design and governance of event-driven systems including both Solace and Kafka-based event broker environments. -
38
Integrate.io
Integrate.io
Unify Your Data Stack: Experience the first no-code data pipeline platform and power enlightened decision making. Integrate.io is the only complete set of data solutions & connectors for easy building and managing of clean, secure data pipelines. Increase your data team's output with all of the simple, powerful tools & connectors you’ll ever need in one no-code data integration platform. Empower any size team to consistently deliver projects on-time & under budget. We ensure your success by partnering with you to truly understand your needs & desired outcomes. Our only goal is to help you overachieve yours. Integrate.io's Platform includes: -No-Code ETL & Reverse ETL: Drag & drop no-code data pipelines with 220+ out-of-the-box data transformations -Easy ELT & CDC :The Fastest Data Replication On The Market -Automated API Generation: Build Automated, Secure APIs in Minutes - Data Warehouse Monitoring: Finally Understand Your Warehouse Spend - FREE Data Observability: Custom -
39
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. -
40
ETL DataHub
ETL
DataHub from ETL Solutions is an enterprise-grade data integration, orchestration, and management platform designed to help organizations connect, harmonize, and operationalize data from diverse sources into a unified, governed, and accessible ecosystem. It enables seamless ingestion and transformation of structured and unstructured data through pre-built connectors and mappings, automated workflows, change data capture, and real-time data pipelines that support analytics, reporting, and AI/ML use cases. Built for hybrid and multi-cloud environments, DataHub centralizes metadata and business logic while enforcing data governance, lineage, and quality controls so stakeholders can trust and act on enterprise data. Its orchestration engine handles complex dependencies and schedules, ensuring data arrives on time and maintains consistency across systems. -
41
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. -
42
CData Sync
CData Software
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 -
43
Conduktor
Conduktor
We created Conduktor, the all-in-one friendly interface to work with the Apache Kafka ecosystem. Develop and manage Apache Kafka with confidence. With Conduktor DevTools, the all-in-one Apache Kafka desktop client. Develop and manage Apache Kafka with confidence, and save time for your entire team. Apache Kafka is hard to learn and to use. Made by Kafka lovers, Conduktor best-in-class user experience is loved by developers. Conduktor offers more than just an interface over Apache Kafka. It provides you and your teams the control of your whole data pipeline, thanks to our integration with most technologies around Apache Kafka. Provide you and your teams the most complete tool on top of Apache Kafka. -
44
Aiven for Apache Kafka
Aiven
Apache Kafka as a fully managed service, with zero vendor lock-in and a full set of capabilities to build your streaming pipeline. Set up fully managed Kafka in less than 10 minutes — directly from our web console or programmatically via our API, CLI, Terraform provider or Kubernetes operator. Easily connect it to your existing tech stack with over 30 connectors, and feel confident in your setup with logs and metrics available out of the box via the service integrations. A fully managed distributed data streaming platform, deployable in the cloud of your choice. Ideal for event-driven applications, near-real-time data transfer and pipelines, stream analytics, and any other case where you need to move a lot of data between applications — and quickly. With Aiven’s hosted and managed-for-you Apache Kafka, you can set up clusters, deploy new nodes, migrate clouds, and upgrade existing versions — in a single mouse click — and monitor them through a simple dashboard.Starting Price: $200 per month -
45
DataKitchen
DataKitchen
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. -
46
Crosser
Crosser Technologies
Analyze and act on your data in the Edge. Make Big Data small and relevant. Collect sensor data from all your assets. Connect any sensor, PLC, DCS, MES or Historian. Condition monitoring of remote assets. Industry 4.0 data collection & integration. Combine streaming and enterprise data in data flows. Use your favorite Cloud Provider or your own data center for storage of data. Bring, manage and deploy your own ML models with Crosser Edge MLOps functionality. The Crosser Edge Node is open to run any ML framework. Central resource library for your trained models in crosser cloud. Drag-and-drop for all other steps in the data pipeline. One operation to deploy ML models to any number of Edge Nodes. Self-Service Innovation powered by Crosser Flow Studio. Use a rich library of pre-built modules. Enables collaboration across teams and sites. No more dependencies on single team members. -
47
Etleap
Etleap
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. -
48
Astro by Astronomer
Astronomer
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. -
49
FLIP
Kanerika
Flip, Kanerika's AI-powered Data Operations Platform, simplifies the complexity of data transformation with its low-code/no-code approach. Designed to help organizations build data pipelines seamlessly, Flip offers flexible deployment options, a user-friendly interface, and a cost-effective pay-per-use pricing model. Empowering businesses to modernize their IT strategies, Flip accelerates data processing and automation, unlocking actionable insights faster. Whether you aim to streamline workflows, enhance decision-making, or stay competitive, Flip ensures your data works harder for you in today’s dynamic landscape.Starting Price: $1614/month -
50
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.