Distributed, fault tolerant, high throughput pub-sub messaging system
An end-to-end data integration platform to build, run, monitor and manage smart data pipelines that deliver continuous data for DataOps. | It is a next-generation data analytics and business intelligence platform that excels at rapidly delivering business value from transactional data and is the first real breakthrough in data analytics in 20 years. It provides an integrated end-to-end data experience, from data acquisition and enrichment to visualizing and sharing results. It cuts project implementation time from months to weeks, provides revolutionary query speed, and maintains a unified, single-source of truth for multiple workloads including business intelligence, analytics, and machine learning. |
Only StreamSets provides a single design experience for all design patterns (batch, streaming, CDC, ETL, ELT, and ML pipelines) for 10x greater developer productivity; smart data pipelines that are resilient to change for 80% less breakages; and a single pane of glass for managing and monitoring all pipelines across hybrid and cloud architectures to eliminate blind spots and control gaps. | Extensible connector architecture;
Parallel data loading;
Direct data mapping;
Embedded notebooks;
Machine learning;
Spark;
Business views;
Materialized views;
Enterprise security;
Query editor;
Dashboards;
3rd party tool support;
REST API;
Parquet data lake;
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Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.

Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well.

It is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating.

Transmit any volume of data, at any level of throughput, without losing messages or requiring other services to be always available. With SQS, you can offload the administrative burden of operating and scaling a highly available messaging cluster, while paying a low price for only what you use.

NSQ is a realtime distributed messaging platform designed to operate at scale, handling billions of messages per day. It promotes distributed and decentralized topologies without single points of failure, enabling fault tolerance and high availability coupled with a reliable message delivery guarantee. See features & guarantees.

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

Apache ActiveMQ is fast, supports many Cross Language Clients and Protocols, comes with easy to use Enterprise Integration Patterns and many advanced features while fully supporting JMS 1.1 and J2EE 1.4. Apache ActiveMQ is released under the Apache 2.0 License.

The 0MQ lightweight messaging kernel is a library which extends the standard socket interfaces with features traditionally provided by specialised messaging middleware products. 0MQ sockets provide an abstraction of asynchronous message queues, multiple messaging patterns, message filtering (subscriptions), seamless access to multiple transport protocols and more.

Distributed SQL Query Engine for Big Data