Risingwave Labs is an early-stage start-up that innovates next-generation database systems. The company develops RisingWave, a cloud-native sql streaming database for modern real-time applications. RisingWave is a cloud-native streaming database that uses sql as the interface language. It is designed to reduce the complexity and cost of building real-time applications. RisingWave consumes streaming data, performs continuous queries, and updates results dynamically. As a database system, RisingWave maintains results inside its own storage and allows users to access data efficiently. Risingwave Labs was founded in early 2021 by a team of experienced database researchers and practitioners who have previously worked for the likes of, AWS Redshift, Microsoft Azure, Snowflake, LinkedIn, Uber, etc. Risingwave Labs has raised tens of millions of us dollars from top-tier vc funds and angels.

Risingwave Labs develops RisingWave, a cloud-native SQL streaming database for modern real-time applications. It is a cloud-native streaming database that uses SQL as the interface language, designed to reduce the complexity and cost of building real-time applications.

Popsink is building the next generation of data processing tools for the modern data stack. Come discover the power of real-time ETLs and automate your decision making.

Build your first real-time ETL in under a minute!

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 is the fully managed Amazon Web Service (AWS) offering for real-time processing of big data.

Provider of software development services

Apache Kafka is a distributed commit log for fast, fault-tolerant communication between producers and consumers using message based topics.

Apache Flink is an open source project of The Apache Software Foundation (ASF). The Apache Flink project originated from the Stratosphere research project.

Apache Flink is an open-source, unified stream-processing and batch-processing framework developed by the Apache Software Foundation.

Google Cloud Dataflow is a cloud-based data processing service for both batch and real-time data streaming applications. It enables developers to set up processing pipelines for integrating, preparing and analyzing large data sets, such as those found in Web analytics or big data analytics applications.
The Cloud Dataflow software expands on earlier Google parallel processing projects, including MapReduce, which originated at the company. Cloud Dataflow is designed to bring to entire analytics pipelines the style of fast parallel execution that MapReduce brought to a single type of computational sort for batch processing jobs. 

Google Cloud Dataflow is a cloud-based data processing service for both batch and real-time data streaming applications.

Redpanda is the modern streaming data platform for developers. API-compatible with Apache Kafka, the product has a breakthrough architecture with 10x lower latencies, single binary deployment with built-in features, and tiered storage in the cloud with a unified streaming API. Redpanda offers a free community edition and commercial options for both self-hosted and SaaS.


Redpanda is the modern streaming data platform for developers, built to be Kafka-compatible, simple, fast, and reliable.

Confluent provides a real-time data stream platform on Apache Kafka. The platform offers an open-source technology that acts as a real-time, fault-tolerant, and highly scalable messaging system, enabling companies to move data from isolated systems into a real-time data pipeline where they can act on it. Audi, Tivo, and Euronext are some of its clients.

Confluent is building the foundational platform for data in motion so any organization can innovate and win in a digital-first world.

ksqlDB provides event streaming database for process application. It allows users to stream database and collect data using SQL statements. Other solutions include team to manage transformations and construct streaming applications.

ksqlDB enables you to build event streaming applications leveraging your familiarity with relational databases.

StreamSets offers a platform dedicated to building smart data pipelines to power DataOps across hybrid and multi-cloud architectures.

StreamSets DataOps Platform enables you to deliver uninterrupted data to every part of your business with smart data pipelines 

Hazelcast is a data infrastructure company that develops, distributes and supports an in-memory data grid and is a Nosql product. Their product, Hazelcast, is an open source build to be used for transactional, scale-out applications. Hazelcast's revenue model is by providing licensed enterprise extension, management center and training and development and deployments.  The company was founded in Palo Alto, CA in 2008, with an office in Istanbul, Turkey.

Hazelcast is the industry leading in-memory computing platform.

Faust is a stream processing library, porting the ideas from Kafka Streams to Python. It is used at Robinhood to build high performance distributed systems and real-time data pipelines that process billions of events every day. Faust provides both stream processing and event processing, sharing similarity with tools such as Kafka Streams, Apache Spark/Storm/Samza/Flink,

StreamNative is founded by the original developers of Apache Pulsar and Apache BookKeeper.It builds a cloud-native event streaming platform that enables enterprises to easily access data as real-time event streams.

The unified messaging and streaming platform
made by the creators of Apache Pulsar.

Decodable’s mission is to make streaming data engineering easy. Decodable delivers the first self-service real-time data platform — that anyone can run.  As a serverless platform for real-time data ingestion, integration, analysis, and event-driven service development, Decodable eliminates the need for a large data team, clusters to set up, or code to write.


Decodable is a serverless real-time data platform. No clusters to set up. No code to write.

InfinyOn, a technology company located in Silicon Valley, is on a mission to accelerate the world's transition to the real-time economy. We have built a modern real-time data platform with a powerful event stream processing engine that gives architects, data engineers, and developers the ability to build the next generation of real-time services.

InfyOn has built event streaming platform that allows architects, data engineers, and developers to build intelligent data pipelines for real-time services.

GridGain enables organizations to accelerate data processing in their Hadoop deployments by providing an in-memory platform. The platform can be used as a database, a stream computing platform, a messaging platform or an accelrator for hadoop based computations. GridGain's in-memory file system accelerates I/O in the Hadoop stack. GridGain requires zero code change to existing MapReduce code for similar performance improvement. It also offers a management and monitoring tool called GridGain Visor for its Hadoop accelerator platform. It is built on top of Apache Ignite, an In-Memory data Fabric. Its clients include Apple, Avis, Canon, IHG, McGraw-Hill Education, Moody's KMV, Sberbank, Sony, TomTom, and Worldpay. The company was named a 'Cool Vendor' for In-Memory Computing Technologies by Gartner in 2014. Gridgain has incubated and open sourced the In-Memory platform in Apache as Ignite.

The GridGain In-Memory Computing Platform is a comprehensive solution provides speed and scalability for data intensive applications across any data store.

GigaSpaces Technologies, Inc. provides application platforms for Java and .Net environments. The company's products include XAP In-Memory Data Grid. XAP In-Memory Data Grid, provides an in-memory cache for fast data access, and an advanced distributed cache for performance and scalability. It serves investment banks, exchanges, market data providers, hedge funds, retail banks, telecommunications and mobile carriers, Web-commerce and online gaming enterprises, and Internet media organizations. GigaSpaces Technologies, Inc. was formerly known as J-Spaces.

GigaSpaces provides the leading in-memory computing platform for fast data analytics and extreme transaction processing.

Meroxa is a real-time data platform that gives data teams the tools they need to build real-time infrastructure in minutes, not months.

Meroxa makes real-time data infrastructure accessible to any company regardless of expertise or available resource.

FASTDATA is a big data analytics platform that leverages GPUs to enable real-time stream data processing. It provides API access to developers to enable stream processing. The firm claims that when its platform is coupled with parallel GPU servers, data processing is 5X faster. The solution finds applications for streaming data processing across areas such as finance, fraud, security, AI, ML, VR/AR, and IoT.

Fastdata.io is developing the world's fastest and most efficient real-time stream processing software engine.

Kx offers a high-performance column-store database with a built-in expressive query and programming language, It is used as a central repository to store time-series data within an enterprise, kdb+ supports real-time analysis of billions of records and fast access to terabytes of historical data. Some of its customers are Goldman Sachs, Morgan Stanley, Merrill Lynch, J.P. Morgan, Deutsche Bank, etc.

The leading provider of time-series database technology, Kx delivers high-speed processing of real-time, streaming and historical data.

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 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 .

Materialize is a cloud-based streaming data analytics platform. The product offered by the company is a platform for SQL on streaming data. The features of the product include reusing of skills from traditional SQL queries and applications, data denormalization, application development, alerts, and notifications, real-time data visualizations, task automation, etc.

Materialize simplifies application development with streaming data. Materialize is powered by Timely Dataflow.

Apache Samza is an open-source, near-realtime, asynchronous computational framework for stream processing developed by the Apache Software Foundation in Scala and Java. It has been developed in conjunction with Apache Kafka. Both were originally developed by LinkedIn.

Apache Samza is a distributed stream processing framework.

Apache Beam is an open source, unified model for defining both batch and streaming data-parallel processing pipelines. Using one of the open source Beam SDKs, you build a program that defines the pipeline. The pipeline is then executed by one of Beam’s supported distributed processing back-ends, which include Apache Flink, Apache Spark, and Google Cloud Dataflow.

Apache Beam - portable, parallel, powerful data processing pipelines. 

Brooklin is a distributed system intended for streaming data between various heterogeneous source and destination systems with high reliability and throughput at scale. Designed for multitenancy, Brooklin can power hundreds of simultaneous data pipelines across different systems and can be easily extended to support new sources and destinations.

An extensible distributed system for reliable nearline data streaming at scale

Ververica provides Ververica Platform, with open source Apache Flink and Application Manager, to the enterprise. Ververica platform enables high-throughput and low-latency solutions for event-driven applications.

Ververica Platform enables every enterprise to take advantage and derive immediate insight from its data in real time.

Companies

Risingwave Labs

Popsink

AWS Kinesis

Apache Kafka

Apache Flink

Google Cloud Dataflow

Redpanda

Confluent

KsqlDB

StreamSets

hazelcast

Faust

StreamNative

Decodable

InfinyOn

Gridgain

Giga Spaces

Meroxa

Fast Data

Kx Systems

Apache Storm

Materialize

Samza

Beam

Brooklin

Ververica

Did we miss any company?