Best Real-Time Data Streaming Tools for OpenMetadata

Compare the Top Real-Time Data Streaming Tools that integrate with OpenMetadata as of October 2025

This a list of Real-Time Data Streaming tools that integrate with OpenMetadata. Use the filters on the left to add additional filters for products that have integrations with OpenMetadata. View the products that work with OpenMetadata in the table below.

What are Real-Time Data Streaming Tools for OpenMetadata?

Real-time data streaming tools enable organizations, big data and machine learning professionals, and data scientists to stream data in real time, and build data models when new data is created or ingested. Compare and read user reviews of the best Real-Time Data Streaming tools for OpenMetadata currently available using the table below. This list is updated regularly.

  • 1
    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.
  • 2
    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.
    Starting Price: Free
  • 3
    Databricks Data Intelligence Platform
    The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker.
  • 4
    Amazon Kinesis
    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.
  • 5
    Apache NiFi

    Apache NiFi

    Apache Software Foundation

    An easy to use, powerful, and reliable system to process and distribute data. Apache NiFi supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic. Some of the high-level capabilities and objectives of Apache NiFi include web-based user interface, offering a seamless experience between design, control, feedback, and monitoring. Highly configurable, loss tolerant, low latency, high throughput, and dynamic prioritization. Flow can be modified at runtime, back pressure, data provenance, track dataflow from beginning to end, designed for extension. Build your own processors and more. Enables rapid development and effective testing. Secure, SSL, SSH, HTTPS, encrypted content, and much more. Multi-tenant authorization and internal authorization/policy management. NiFi is comprised of a number of web applications (web UI, web API, documentation, custom UI's, etc). So, you'll need to set up your mapping to the root path.
  • 6
    Redpanda

    Redpanda

    Redpanda Data

    Breakthrough data streaming capabilities that let you deliver customer experiences never before possible. Kafka API and ecosystem are compatible. Redpanda BulletPredictable low latencies with zero data loss. Redpanda BulletUpto 10x faster than Kafka. Redpanda BulletEnterprise-grade support and hotfixes. Redpanda BulletAutomated backups to S3/GCS. Redpanda Bullet100% freedom from routine Kafka operations. Redpanda BulletSupport for AWS and GCP. Redpanda was designed from the ground up to be easily installed to get streaming up and running quickly. After you see its power, put Redpanda to the test in production. Use the more advanced Redpanda features. We manage provisioning, monitoring, and upgrades. Without any access to your cloud credentials. Sensitive data never leaves your environment. Provisioned, operated, and maintained for you. Configurable instance types. Expand cluster as your needs grow.
  • Previous
  • You're on page 1
  • Next