Alternatives to Apache NiFi

Compare Apache NiFi alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Apache NiFi in 2026. Compare features, ratings, user reviews, pricing, and more from Apache NiFi competitors and alternatives in order to make an informed decision for your business.

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    StarTree

    StarTree

    StarTree

    StarTree, powered by Apache Pinot™, is a fully managed real-time analytics platform built for customer-facing applications that demand instant insights on the freshest data. Unlike traditional data warehouses or OLTP databases—optimized for back-office reporting or transactions—StarTree is engineered for real-time OLAP at true scale, meaning: - Data Volume: query performance sustained at petabyte scale - Ingest Rates: millions of events per second, continuously indexed for freshness - Concurrency: thousands to millions of simultaneous users served with sub-second latency With StarTree, businesses deliver always-fresh insights at interactive speed, enabling applications that personalize, monitor, and act in real time.
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    IRI Voracity

    IRI Voracity

    IRI, The CoSort Company

    Voracity is the only high-performance, all-in-one data management platform accelerating AND consolidating the key activities of data discovery, integration, migration, governance, and analytics. Voracity helps you control your data in every stage of the lifecycle, and extract maximum value from it. Only in Voracity can you: 1) CLASSIFY, profile and diagram enterprise data sources 2) Speed or LEAVE legacy sort and ETL tools 3) MIGRATE data to modernize and WRANGLE data to analyze 4) FIND PII everywhere and consistently MASK it for referential integrity 5) Score re-ID risk and ANONYMIZE quasi-identifiers 6) Create and manage DB subsets or intelligently synthesize TEST data 7) Package, protect and provision BIG data 8) Validate, scrub, enrich and unify data to improve its QUALITY 9) Manage metadata and MASTER data. Use Voracity to comply with data privacy laws, de-muck and govern the data lake, improve the reliability of your analytics, and create safe, smart test data
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    Striim

    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.
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    Cribl AppScope
    AppScope is a new approach to black-box instrumentation delivering ubiquitous, unified telemetry from any Linux executable by simply prepending scope to the command. Talk to any customer using Application Performance Management, and they’ll tell you how much they love their solution, but they wish they could extend it to more of their applications. Most have 10% or fewer of their apps instrumented for APM, and are supplementing what they can with basic metrics. Where does this leave the other 80%? Enter AppScope. No language-specific instrumentation. No application developers required. AppScope is language agnostic and completely userland; works with any application; scales from the CLI to production. Send AppScope data to any existing monitoring tool, time series database, or log tool. AppScope allows SREs and Ops teams to interrogate running applications to discover how they work and their behavior in any deployment context, from on-prem to cloud to containers.
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    Kestra

    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.
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    Apache Flink

    Apache Flink

    Apache Software Foundation

    Apache Flink is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams. Flink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale. Any kind of data is produced as a stream of events. Credit card transactions, sensor measurements, machine logs, or user interactions on a website or mobile application, all of these data are generated as a stream. Apache Flink excels at processing unbounded and bounded data sets. Precise control of time and state enable Flink’s runtime to run any kind of application on unbounded streams. Bounded streams are internally processed by algorithms and data structures that are specifically designed for fixed sized data sets, yielding excellent performance. Flink is designed to work well each of the previously listed resource managers.
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    IBM StreamSets
    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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    Apache Airflow

    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.
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    Apache Beam

    Apache Beam

    Apache Software Foundation

    The easiest way to do batch and streaming data processing. Write once, run anywhere data processing for mission-critical production workloads. Beam reads your data from a diverse set of supported sources, no matter if it’s on-prem or in the cloud. Beam executes your business logic for both batch and streaming use cases. Beam writes the results of your data processing logic to the most popular data sinks in the industry. A simplified, single programming model for both batch and streaming use cases for every member of your data and application teams. Apache Beam is extensible, with projects such as TensorFlow Extended and Apache Hop built on top of Apache Beam. Execute pipelines on multiple execution environments (runners), providing flexibility and avoiding lock-in. Open, community-based development and support to help evolve your application and meet the needs of your specific use cases.
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    Apache Gobblin

    Apache Gobblin

    Apache Software Foundation

    A distributed data integration framework that simplifies common aspects of Big Data integration such as data ingestion, replication, organization, and lifecycle management for both streaming and batch data ecosystems. Runs as a standalone application on a single box. Also supports embedded mode. Runs as an mapreduce application on multiple Hadoop versions. Also supports Azkaban for launching mapreduce jobs. Runs as a standalone cluster with primary and worker nodes. This mode supports high availability and can run on bare metals as well. Runs as an elastic cluster on public cloud. This mode supports high availability. Gobblin as it exists today is a framework that can be used to build different data integration applications like ingest, replication, etc. Each of these applications is typically configured as a separate job and executed through a scheduler like Azkaban.
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    Apache Kafka

    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.
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    Apache Storm

    Apache Storm

    Apache Software Foundation

    Apache Storm is a free and open source distributed realtime computation system. Apache Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Apache Storm is simple, can be used with any programming language, and is a lot of fun to use! Apache Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Apache Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate. Apache Storm integrates with the queueing and database technologies you already use. An Apache Storm topology consumes streams of data and processes those streams in arbitrarily complex ways, repartitioning the streams between each stage of the computation however needed. Read more in the tutorial.
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    Cloudera DataFlow
    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.
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    Data Flow Manager
    Data Flow Manager is an Agentic AI Control Plane for Apache NiFi Operations, built for enterprises running NiFi at real scale. Run, manage, and fix NiFi challenges across all clusters, environments, and flows using simple natural-language prompts. One platform. One control plane. Zero firefighting. DFM replaces fragmented UIs, brittle scripts, and reactive operations with centralized, AI-driven control, enabling NiFi teams to transition from manual operations to governed, autonomous execution. What DFM delivers: • Centralized control across all NiFi clusters and environments • Prompt-driven flow deployment and promotion • Pre-deploy flow validation & sanity checks • Scheduled and controlled flow deployments • Centralized controller service management • Built-in approval workflows and RBAC • Immutable, detailed audit logs • Unified visibility into flow health and runtime state
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    Datavolo

    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
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    Google Cloud Dataflow
    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.
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    Confluent

    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.
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    Kylo

    Kylo

    Teradata

    Kylo is an open source enterprise-ready data lake management software platform for self-service data ingest and data preparation with integrated metadata management, governance, security and best practices inspired by Think Big's 150+ big data implementation projects. Self-service data ingest with data cleansing, validation, and automatic profiling. Wrangle data with visual sql and an interactive transform through a simple user interface. Search and explore data and metadata, view lineage, and profile statistics. Monitor health of feeds and services in the data lake. Track SLAs and troubleshoot performance. Design batch or streaming pipeline templates in Apache NiFi and register with Kylo to enable user self-service. Organizations can expend significant engineering effort moving data into Hadoop yet struggle to maintain governance and data quality. Kylo dramatically simplifies data ingest by shifting ingest to data owners through a simple guided UI.
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    DataOps DataFlow
    A holistic component-based platform for automating Data Reconciliation tests in modern Data Lake and Cloud Data Migration projects using Apache Spark. DataOps DataFlow is a modern, web browser-based solution for automating the testing of ETL, Data Warehouse, and Data Migration projects. Use Dataflow to inject data from any of the varied data sources, compare data, and load differences to S3 or a database. With fast and easy to set up, create and run dataflow in minutes. A best in the class testing tool for Big Data Testing DataOps DataFlow can integrate with all modern and advanced data sources including RDBMS, NoSQL, Cloud, and File-Based.
    Starting Price: Contact us
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    3forge

    3forge

    3forge

    Your enterprise's issues may be complex. That doesn't mean building the solution has to be. 3forge is the highly-flexible, low-code platform that empowers enterprise application development in record time. Reliability? Check. Scalability? That too. Deliverability? In record time. Even for the most complex work flows and data sets. With 3forge, you no longer have to choose. Data integration, virtualization, processing, visualization, and workflows all living in one place - solving the world's most complex real-time streaming data challenges. 3forge provides award-winning technology that enables developers to deploy mission-critical applications in record time. Experience the difference of real-time data and zero latency with 3forge's focus on data integration, virtualization, processing, and visualization.
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    Samza

    Samza

    Apache Software Foundation

    Samza allows you to build stateful applications that process data in real-time from multiple sources including Apache Kafka. Battle-tested at scale, it supports flexible deployment options to run on YARN or as a standalone library. Samza provides extremely low latencies and high throughput to analyze your data instantly. Scales to several terabytes of state with features like incremental checkpoints and host-affinity. Samza is easy to operate with flexible deployment options - YARN, Kubernetes or standalone. Ability to run the same code to process both batch and streaming data. Integrates with several sources including Kafka, HDFS, AWS Kinesis, Azure Eventhubs, K-V stores and ElasticSearch.
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    Amazon Managed Service for Apache Flink
    Thousands of customers use Amazon Managed Service for Apache Flink to run stream processing applications. With Amazon Managed Service for Apache Flink, you can transform and analyze streaming data in real-time using Apache Flink and integrate applications with other AWS services. There are no servers and clusters to manage, and there is no computing and storage infrastructure to set up. You pay only for the resources you use. Build and run Apache Flink applications, without setting up infrastructure and managing resources and clusters. Process gigabytes of data per second with subsecond latencies and respond to events in real-time. Deploy highly available and durable applications with Multi-AZ deployments and APIs for application lifecycle management. Develop applications that transform and deliver data to Amazon Simple Storage Service (Amazon S3), Amazon OpenSearch Service, and more.
    Starting Price: $0.11 per hour
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    CloverDX

    CloverDX

    CloverDX

    Design, debug, run and troubleshoot data transformations and jobflows in a developer-friendly visual designer. Orchestrate data workloads that require tasks to be carried out in the right sequence, orchestrate multiple systems with the transparency of visual workflows. Deploy data workloads easily into a robust enterprise runtime environment. In cloud or on-premise. Make data available to people, applications and storage under a single unified platform. Manage your data workloads and related processes together in a single platform. No task is too complex. We’ve built CloverDX on years of experience with large enterprise projects. Developer-friendly open architecture and flexibility lets you package and hide the complexity for non-technical users. Manage the entire lifecycle of a data pipeline from design, deployment to evolution and testing. Get things done fast with the help of our in-house customer success teams.
    Starting Price: $5000.00/one-time
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    Apache Flume

    Apache Flume

    Apache Software Foundation

    Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. It has a simple and flexible architecture based on streaming data flows. It is robust and fault-tolerant with tunable reliability mechanisms and many failovers and recovery mechanisms. It uses a simple extensible data model that allows for online analytic applications. The Apache Flume team is pleased to announce the release of Flume 1.8.0. Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of streaming event data.
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    TapData

    TapData

    TapData

    CDC-based live data platform for heterogeneous database replication, real-time data integration, or building a real-time data warehouse. By using CDC to sync production line data stored in DB2 and Oracle to the modern database, TapData enabled an AI-augmented real-time dispatch software to optimize the semiconductor production line process. The real-time data made instant decision-making in the RTD software a possibility, leading to faster turnaround times and improved yield. As one of the largest telcos, customer has many regional systems that cater to the local customers. By syncing and aggregating data from various sources and locations into a centralized data store, customers were able to build an order center where the collective orders from many applications can now be aggregated. TapData seamlessly integrates inventory data from 500+ stores, providing real-time insights into stock levels and customer preferences, enhancing supply chain efficiency.
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    Estuary Flow
    Estuary Flow is a new kind of DataOps platform that empowers engineering teams to build real-time, data-intensive applications at scale with minimal friction. This platform unifies a team’s databases, pub/sub systems, and SaaS around their data, without requiring new investments in infrastructure or development.
    Starting Price: $200/month
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    Talend Open Studio
    With Talend Open Studio, you can begin building basic data pipelines in no time. Execute simple ETL and data integration tasks, get graphical profiles of your data, and manage files — from a locally installed, open-source environment that you control. If your project is ready to go, jump right in with Talend Cloud. You get the same easy-to-use interface of Open Studio, plus the tools for collaboration, monitoring, and scheduling that ongoing projects require. You can easily add data quality, big data integration, and processing resources, and take advantage of the latest data sources, analytics technologies, and elastic capacity from AWS or Azure when you need it. Join the Talend Community and start your data integration journey on the right foot. Whether you’re a beginner or an expert, the Talend Community is the place to share best practices and hunt for new tricks you haven’t tried.
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    SelectDB

    SelectDB

    SelectDB

    SelectDB is a modern data warehouse based on Apache Doris, which supports rapid query analysis on large-scale real-time data. From Clickhouse to Apache Doris, to achieve the separation of the lake warehouse and upgrade to the lake warehouse. The fast-hand OLAP system carries nearly 1 billion query requests every day to provide data services for multiple scenes. Due to the problems of storage redundancy, resource seizure, complicated governance, and difficulty in querying and adjustment, the original lake warehouse separation architecture was decided to introduce Apache Doris lake warehouse, combined with Doris's materialized view rewriting ability and automated services, to achieve high-performance data query and flexible data governance. Write real-time data in seconds, and synchronize flow data from databases and data streams. Data storage engine for real-time update, real-time addition, and real-time pre-polymerization.
    Starting Price: $0.22 per hour
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    Apache Doris

    Apache Doris

    The Apache Software Foundation

    Apache Doris is a modern data warehouse for real-time analytics. It delivers lightning-fast analytics on real-time data at scale. Push-based micro-batch and pull-based streaming data ingestion within a second. Storage engine with real-time upsert, append and pre-aggregation. Optimize for high-concurrency and high-throughput queries with columnar storage engine, MPP architecture, cost based query optimizer, vectorized execution engine. Federated querying of data lakes such as Hive, Iceberg and Hudi, and databases such as MySQL and PostgreSQL. Compound data types such as Array, Map and JSON. Variant data type to support auto data type inference of JSON data. NGram bloomfilter and inverted index for text searches. Distributed design for linear scalability. Workload isolation and tiered storage for efficient resource management. Supports shared-nothing clusters as well as separation of storage and compute.
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    Qlik Replicate
    Qlik Replicate is a high-performance data replication tool offering optimized data ingestion from a broad array of data sources and platforms and seamless integration with all major big data analytics platforms. Replicate supports bulk replication as well as real-time incremental replication using CDC (change data capture). Our unique zero-footprint architecture eliminates unnecessary overhead on your mission-critical systems and facilitates zero-downtime data migrations and database upgrades. Database replication enables you to move or consolidate data from a production database to a newer version of the database, another type of computing environment, or an alternative database management system, to migrate data from SQL Server to Oracle, for example. Data replication can be used to offload production data from a database, and load it to operational data stores or data warehouses for reporting or analytics.
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    Apache Synapse

    Apache Synapse

    Apache Software Foundation

    Apache Synapse is a lightweight and high-performance Enterprise Service Bus (ESB). Powered by a fast and asynchronous mediation engine, Apache Synapse provides exceptional support for XML, Web Services and REST. In addition to XML and SOAP, Apache Synapse supports several other content interchange formats, such as plain text, binary, Hessian and JSON. The wide range of transport adapters available for Synapse, enables it to communicate over many application and transport layer protocols. As of now, Apache Synapse supports HTTP/S, Mail (POP3, IMAP, SMTP), JMS, TCP, UDP, VFS, SMS, XMPP and FIX. High-performing PassThrough HTTP transport support for all mediation scenarios. Ultra-fast, low latency mediation of HTTP requests. Supporting a very large number of inbound (client -> ESB) and outbound (ESB -> server) connections concurrently. Intelligently handle message content and content awareness built into the engine with shared buffer for handling data.
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    Astra Streaming
    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.
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    HarperDB

    HarperDB

    HarperDB

    HarperDB is a distributed systems platform that combines database, caching, application, and streaming functions into a single technology. With it, you can start delivering global-scale back-end services with less effort, higher performance, and lower cost than ever before. Deploy user-programmed applications and pre-built add-ons on top of the data they depend on for a high throughput, ultra-low latency back end. Lightning-fast distributed database delivers orders of magnitude more throughput per second than popular NoSQL alternatives while providing limitless horizontal scale. Native real-time pub/sub communication and data processing via MQTT, WebSocket, and HTTP interfaces. HarperDB delivers powerful data-in-motion capabilities without layering in additional services like Kafka. Focus on features that move your business forward, not fighting complex infrastructure. You can't change the speed of light, but you can put less light between your users and their data.
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    WhereScape

    WhereScape

    WhereScape Software

    WhereScape helps IT organizations of all sizes leverage automation to design, develop, deploy, and operate data infrastructure faster. More than 700 customers worldwide rely on WhereScape automation to eliminate hand-coding and other repetitive, time-intensive aspects of data infrastructure projects to deliver data warehouses, vaults, lakes and marts in days or weeks rather than in months or years. From data warehouses and vaults to data lakes and marts, deliver data infrastructure and big data integration fast. Quickly and easily plan, model and design all types of data infrastructure projects. Use sophisticated data discovery and profiling capabilities to bulletproof design and rapid prototyping to collaborate earlier with business users. Fast-track the development, deployment and operation of your data infrastructure projects. Dramatically reduce the delivery time, effort, cost and risk of new projects, and better position projects for future business change.
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    Precisely Connect
    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.
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    Flatfile

    Flatfile

    Flatfile

    Flatfile is an AI-powered data exchange platform designed to streamline the collection, mapping, cleaning, transformation, and conversion of data for enterprises. It offers a rich library of smart APIs for file-based data import, enabling developers to integrate its capabilities seamlessly into their applications. The platform provides an intuitive, workbook-style user experience, facilitating user-friendly data management with features like search, find and replace, and sort functionalities. Flatfile ensures compliance with industry standards, being SOC 2, HIPAA, and GDPR compliant, and operates on secure cloud infrastructure for scalability and performance. By automating data transformations and validations, Flatfile reduces manual effort, accelerates data onboarding processes, and enhances data quality across various industries.
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    Adoki

    Adoki

    Adastra

    Adoki streamlines data transfers to and from any platform or system—whether it's a data warehouse, database, cloud service, Hadoop platform, or streaming application—on both one-time and recurring schedules. It adapts to your IT infrastructure's workload, adjusting transfer or replication processes to optimal times when needed. With centralized management and monitoring of data transfers, Adoki allows you to handle your data operations with a smaller, more efficient team.
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    Sesame Software

    Sesame Software

    Sesame Software

    Sesame Software specializes in secure, efficient data integration and replication across diverse cloud, hybrid, and on-premise sources. Our patented scalability ensures comprehensive access to critical business data, facilitating a holistic view in the BI tools of your choice. This unified perspective empowers your own robust reporting and analytics, enabling your organization to regain control of your data with confidence. At Sesame Software, we understand what’s at stake when you need to move a massive amount of data between environments quickly—while keeping it protected, maintaining centralized access, and ensuring compliance with regulations. Over the past 30+ years, we’ve helped hundreds of organizations like Proctor & Gamble, Bank of America, and the U.S. government connect, move, store, and protect their data.
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    Spark Streaming

    Spark Streaming

    Apache Software Foundation

    Spark Streaming brings Apache Spark's language-integrated API to stream processing, letting you write streaming jobs the same way you write batch jobs. It supports Java, Scala and Python. Spark Streaming recovers both lost work and operator state (e.g. sliding windows) out of the box, without any extra code on your part. By running on Spark, Spark Streaming lets you reuse the same code for batch processing, join streams against historical data, or run ad-hoc queries on stream state. Build powerful interactive applications, not just analytics. Spark Streaming is developed as part of Apache Spark. It thus gets tested and updated with each Spark release. You can run Spark Streaming on Spark's standalone cluster mode or other supported cluster resource managers. It also includes a local run mode for development. In production, Spark Streaming uses ZooKeeper and HDFS for high availability.
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    Getint

    Getint

    Getint

    Getint is an integration platform that synchronizes data between work management, DevOps, and IT service management systems. It connects tools such as Jira, ServiceNow, Azure DevOps, GitHub, GitLab, Zendesk, monday.com, Salesforce, and many more. The platform supports one-way and two-way synchronization of issues, incidents, tasks, work items, comments, attachments, statuses, and custom fields. Administrators can configure field mappings, filtering rules, and workflow mappings to control how information flows between systems. Getint supports both SaaS and On-Premise deployments, allowing organizations to integrate cloud and self-hosted environments. It includes visual configuration tools, advanced scripting options, and detailed logs for monitoring integrations. Typical use cases include syncing development and support tickets, connecting ITSM and engineering teams, and integrating systems across organizations.
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    IBM Event Streams
    IBM Event Streams is a fully managed event streaming platform built on Apache Kafka, designed to help enterprises process and respond to real-time data streams. With capabilities for machine learning integration, high availability, and secure cloud deployment, it enables organizations to create intelligent applications that react to events as they happen. The platform supports multi-cloud environments, disaster recovery, and geo-replication, making it ideal for mission-critical workloads. IBM Event Streams simplifies building and scaling real-time, event-driven solutions, ensuring data is processed quickly and efficiently.
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    Google Cloud Datastream
    Serverless and easy-to-use change data capture and replication service. Access to streaming data from MySQL, PostgreSQL, AlloyDB, SQL Server, and Oracle databases. Near real-time analytics in BigQuery. Easy-to-use setup with built-in secure connectivity for faster time-to-value. A serverless platform that automatically scales, with no resources to provision or manage. Log-based mechanism to reduce the load and potential disruption on source databases. Synchronize data across heterogeneous databases, storage systems, and applications reliably, with low latency, while minimizing impact on source performance. Get up and running fast with a serverless and easy-to-use service that seamlessly scales up or down, and has no infrastructure to manage. Connect and integrate data across your organization with the best of Google Cloud services like BigQuery, Spanner, Dataflow, and Data Fusion.
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    WarpStream

    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
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    VeloDB

    VeloDB

    VeloDB

    Powered by Apache Doris, VeloDB is a modern data warehouse for lightning-fast analytics on real-time data at scale. Push-based micro-batch and pull-based streaming data ingestion within seconds. Storage engine with real-time upsert、append and pre-aggregation. Unparalleled performance in both real-time data serving and interactive ad-hoc queries. Not just structured but also semi-structured data. Not just real-time analytics but also batch processing. Not just run queries against internal data but also work as a federate query engine to access external data lakes and databases. Distributed design to support linear scalability. Whether on-premise deployment or cloud service, separation or integration of storage and compute, resource usage can be flexibly and efficiently adjusted according to workload requirements. Built on and fully compatible with open source Apache Doris. Support MySQL protocol, functions, and SQL for easy integration with other data tools.
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    Jitterbit

    Jitterbit

    Jitterbit

    Jitterbit Harmony is an AI-infused integration and automation platform designed to unify business systems across cloud, SaaS, and on-premise environments. It provides end-to-end workflow automation through products including iPaaS, API Manager, App Builder, and EDI. With a layered AI architecture, Harmony embeds accountable AI agents and assistants directly into integration processes. Drag-and-drop connectors enable rapid deployment and seamless connectivity with thousands of applications such as Salesforce, SAP, Workday, and NetSuite. The platform supports industries ranging from healthcare and manufacturing to retail and logistics. Jitterbit has earned repeated #1 rankings in G2’s Enterprise iPaaS Implementation Index, highlighting customer satisfaction and speed to value. Designed for secure, scalable transformation, Harmony powers integration, automation, and application development within a single unified system.
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    Enrich.sh

    Enrich.sh

    Enrich.sh

    Enrich.sh is a high-performance data enrichment infrastructure platform as a service designed to power real-time data workflows at scale with minimal latency and high throughput. It enables businesses and developers to enrich, process, and transform large volumes of data (500+ requests per second) with sub-millisecond response times, making it suitable for performance-sensitive and edge-oriented applications. It is built for big data at the edge, offering a backend service that handles enrichment workloads efficiently without the need for heavy operational overhead, allowing teams to focus on core product development rather than infrastructure management. Enrich.sh provides robust APIs that let users ingest, augment, and serve enriched data quickly, supporting complex enrichment strategies and rapid data pipelines for analytical or transactional use cases.
    Starting Price: $49 per month
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    Oracle Cloud Infrastructure Streaming
    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.
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    Amazon Data Firehose
    Easily capture, transform, and load streaming data. Create a delivery stream, select your destination, and start streaming real-time data with just a few clicks. Automatically provision and scale compute, memory, and network resources without ongoing administration. Transform raw streaming data into formats like Apache Parquet, and dynamically partition streaming data without building your own processing pipelines. Amazon Data Firehose provides the easiest way to acquire, transform, and deliver data streams within seconds to data lakes, data warehouses, and analytics services. To use Amazon Data Firehose, you set up a stream with a source, destination, and required transformations. Amazon Data Firehose continuously processes the stream, automatically scales based on the amount of data available, and delivers it within seconds. Select the source for your data stream or write data using the Firehose Direct PUT API.
    Starting Price: $0.075 per month
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    Stackable

    Stackable

    Stackable

    The Stackable data platform was designed with openness and flexibility in mind. It provides you with a curated selection of the best open source data apps like Apache Kafka, Apache Druid, Trino, and Apache Spark. While other current offerings either push their proprietary solutions or deepen vendor lock-in, Stackable takes a different approach. All data apps work together seamlessly and can be added or removed in no time. Based on Kubernetes, it runs everywhere, on-prem or in the cloud. stackablectl and a Kubernetes cluster are all you need to run your first stackable data platform. Within minutes, you will be ready to start working with your data. Configure your one-line startup command right here. Similar to kubectl, stackablectl is designed to easily interface with the Stackable Data Platform. Use the command line utility to deploy and manage stackable data apps on Kubernetes. With stackablectl, you can create, delete, and update components.
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    DeltaStream

    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.