Alibaba JStorm is an enterprise fast and stable streaming process engine. It runs program up to 4x faster than Apache Storm. It is easy to switch from record mode to mini-batch mode. It is not only a streaming process engine. It means one solution for real time requirement, whole realtime ecosystem.


jstorm - Enterprise Stream Process Engine

The Zephyr Project is a scalable real-time operating system (RTOS) supporting multiple hardware architectures, optimized for resource constrained devices, and built with security in mind. The Zephyr OS is based on a small-footprint kernel designed for use on resource-constrained systems: from simple embedded environmental sensors and LED wearables to sophisticated smart watches and IoT wireless gateways.
 
The Zephyr kernel supports multiple architectures, including ARM Cortex-M, Intel x86, ARC, Nios II, Tensilica Xtensa, and RISC-V, and a large number of supported boards. 
 
Its features include Extensive suite of Kernel services, Multiple Scheduling Algorithms, Highly configurable / Modular for flexibility, Cross Architecture, Memory Protection, Compile-time resource definition, Optimized Device Driver Model, Devicetree Support, Bluetooth Low Energy 5.0 support, Non-volatile storage (NVS), Powerful multi-backend logging Framework, Virtual File System Interface with LittleFS and FATFS Support.

The Zephyr Project is a scalable real-time operating system (RTOS) supporting multiple hardware architectures, optimized for resource constrained devices, and built with security in mind. The Zephyr OS is based on a small-footprint kernel designed for use on resource-constrained systems: from simple embedded environmental sensors and LED wearables to sophisticated smart watches and IoT wireless gateways.

Zephyr - Scalable real-time operating system (RTOS) supporting multiple hardware architectures

Vespa is an engine for low-latency computation over large data sets. It stores and indexes your data such that queries, selection and processing over the data can be performed at serving time. Vespa is serving platform for Yahoo.com, Yahoo News, Yahoo Sports, Yahoo Finance, Yahoo Gemini, Flickr.
 Queries can use both structured filters and unstructured text search to select data. All the matching data is then ranked according to a ranking function - typically machine learned - to implement such use cases as search relevance, recommendation, targeting and personalization.
 
Vespa is scalable. System sizes up to hundreds of nodes handling tens of billions of documents are not uncommon, and no harder to set up and modify than single node systems. Since all system components, as well as stored data is redundant and self-correcting, hardware failures are not operational emergencies and can be handled by re-adding capacity when convenient.
Its feature include:
<ul>
<li>Text search - Combine structured query and text search to select data</li>
<li>Advanced Ranking - Machine learned ranking</li>
<li>Aggregation</li>
<li>Elastic, Scalable</li>
<li>High Availability</li>
<li>Auto repair data corruption</li>
<li>Simple HTTP API interface&nbsp;</li>
<li>lot more...</li>
</ul>

Vespa is an engine for low-latency computation over large data sets. It stores and indexes your data such that queries, selection and processing over the data can be performed at serving time. Vespa is serving platform for Yahoo.com, Yahoo News, Yahoo Sports, Yahoo Finance, Yahoo Gemini, Flickr.

Vespa - Yahoo's big data serving engine

ASP.NET SignalR is a library for ASP.NET developers that makes it incredibly simple to add real-time web functionality to your applications. It's the ability to have your server-side code push content to the connected clients as it happens, in real-time. SignalR also provides a very simple, high-level API for doing server to client RPC (call JavaScript functions in your clients' browsers from server-side .NET code) in your ASP.NET application.

SignalR - Incredibly simple real-time web for .NET

ClickHouse is an open source column-oriented database management system capable of real time generation of analytical data reports using SQL queries. It is Linearly Scalable, Blazing Fast, Highly Reliable, Fault Tolerant, Data compression, Real time query processing, Web analytics, Vectorized query execution, Local and distributed joins. It can process hundreds of millions to more than a billion rows and tens of gigabytes of data per single server per second.

ClickHouse - Columnar DBMS and Real Time Analytics

Pilosa is an open source, distributed bitmap index that dramatically accelerates continuous analysis across multiple, massive data sets.  Pilosa collapses the speed and batch layer by abstracting the index from data storage, optimizing it for massive scale, and making your data instantly queryable and continuously analyzable. 

Pilosa - Distributed bitmap index that dramatically accelerates queries across multiple, massive data sets

Hazelcast Jet is a distributed computing platform built for high-performance stream processing and fast batch processing. It embeds Hazelcast In-Memory Data Grid (IMDG) to provide a lightweight, simple-to-deploy package that includes scalable in-memory storage. Hazelcast Jet performs parallel execution to enable data-intensive applications to operate in near real-time.
 
Hazelcast Jet gives you all the infrastructure you need to build a distributed data processing pipeline within one 10Mb Java JAR: processing, storage and clustering. Hazelcast Jet comes with in-memory operational storage that’s available out-of-the box. This storage is partitioned, distributed and replicated across the Hazelcast Jet cluster for capacity and resiliency. It can be used as an input data buffer, to publish the results of a Hazelcast Jet computation, to connect multiple Hazelcast Jet jobs or as a lookup cache for data enrichment.

Hazelcast Jet is a distributed computing platform built for high-performance stream processing and fast batch processing. It embeds Hazelcast In-Memory Data Grid (IMDG) to provide a lightweight, simple-to-deploy package that includes scalable in-memory storage. Hazelcast Jet performs parallel execution to enable data-intensive applications to operate in near real-time.

Hazelcast Jet - A general purpose distributed data processing engine, built on top of Hazelcast.

OmniSciDB is the foundation of the OmniSci platform. OmniSciDB is SQL-based, relational, columnar and specifically developed to harness the massive parallelism of modern CPU and GPU hardware. OmniSciDB can query up to billions of rows in milliseconds, and is capable of unprecedented ingestion speeds, making it the ideal SQL engine for the era of big, high-velocity data.
 
OmniSciDB optimizes the memory and compute layers to deliver unprecedented performance. OmniSciDB was designed to keep hot data in GPU memory for the fastest access possible. Other GPU database systems have taken the approach of storing the data in CPU memory, only moving it to GPU at query time, trading the gains they receive from GPU parallelism with transfer overheads over the PCIe bus.
 
OmniSciDB natively supports standard SQL and returns query results hundreds of times faster than CPU-only analytical database platforms. Analysts and data scientists can still rely on their existing SQL knowledge, querying data using industry-standard SQL.

OmniSciDB is the foundation of the OmniSci platform. OmniSciDB is SQL-based, relational, columnar and specifically developed to harness the massive parallelism of modern CPU and GPU hardware. OmniSciDB can query up to billions of rows in milliseconds, and is capable of unprecedented ingestion speeds, making it the ideal SQL engine for the era of big, high-velocity data.

OmniSciDB - Open Source Analytical Database & SQL Engine

Cube is an open-source system for visualizing time series data. If you send timestamped events (with optional structured data), you can easily build realtime visualizations of aggregate metrics for internal dashboards. For example, you might use Cube to monitor traffic to your website, counting the number of requests in 5-minute intervals.

Cube - Time Series Visualization

Storm is a distributed real time computation system. Storm makes it easy to reliably process unbounded streams of data, doing for real time processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. 
Storm integrates with the queueing and database technologies you already use. A 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.

Storm is a distributed real time computation system. Storm makes it easy to reliably process unbounded streams of data, doing for real time processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. 

Apache Storm - Distributed and fault-tolerant realtime computation

Open Distro for Elasticsearch is an Apache 2.0-licensed distribution of Elasticsearch enhanced with Enterprise Security, Alerting, SQL, Index Management, k-Nearest Neighbor Search, Performance Analyzer and more. 
 
It provides set of features to help you keep your data secure and stay compliant with regulations such as GDPR, HIPAA, PCI, and ISO. Whether you want to encrypt data in-transit, authenticate users against Active Directory, use Kerberos or JSON web tokens for single sign-on (SSO), or monitor and log any malicious access attempts, Open Distro for Elasticsearch has you covered.
 
It provides support to extract insights out of Elasticsearch using the familiar SQL query syntax. Use aggregations, group by, and where clauses to investigate your data. Read your data as JSON documents or CSV tables so you have the flexibility to use the format that works best for you

Open Distro for Elasticsearch is an Apache 2.0-licensed distribution of Elasticsearch enhanced with Enterprise Security, Alerting, SQL, Index Management, k-Nearest Neighbor Search, Performance Analyzer and more. 


Open Distro for Elasticsearch  - Elasticsearch enhanced with enterprise security, alerting, SQL, and more

Kudu is a storage system for tables of structured data. Kudu provides a combination of fast inserts/updates and efficient columnar scans to enable multiple real-time analytic workloads across a single storage layer. As a new complement to HDFS and Apache HBase, Kudu gives architects the flexibility to address a wider variety of use cases without exotic workarounds.

Kudu - Hadoop storage layer to enable fast analytics on fast data

A real-time comment engine with support for anonymous or authenticated posts.

Comments App - A real-time, markdown-enabled comment engine powered by leveldb with oauth support

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