Amazon Kinesis
Apache Flink
Confluent
Apache Kafka
PieSync
Azure Stream Analytics
Spark Streaming
Google Cloud Dataflow
Apache Flume
Fluentd
Apache Flink
Apache Spark
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Based on our record, Amazon Kinesis seems to be a lot more popular than Apache Flume. While we know about 22 links to Amazon Kinesis, we've tracked only 1 mention of Apache Flume. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
When you see Amazon Kinesis as an option, this becomes the ideal option to process data 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... - Source: dev.to / about 1 month ago
RisingWave is an open-source streaming database that has built-in fully-managed CDC source connectors for various databases, also it can collect data from other sources such Kafka, Pulsar, Kinesis, or Redpanda and it allows you to query real-time streams using SQL. You can get a materialized view that is always up-to-date. - Source: dev.to / about 1 year ago
For example, RisingWave is one of the fastest-growing open-source streaming databases that can ingest data from Apache Kafka, Apache Pulsar, Amazon Kinesis, Redpanda, and databases via native Change data capture connections or using Debezium connectors to MySQL and PostgreSQL sources. Previously, I wrote a blog post about how to choose the right streaming database that discusses some key factors that you should... - Source: dev.to / about 1 year ago
RisingWave is an open-source distributed SQL database for stream processing. RisingWave accepts data from sources like Apache Kafka, Apache Pulsar, Amazon Kinesis, Redpanda, and databases via native Change data capture connections to MySQL and PostgreSQL sources. It uses the concept of materialized view that involves caching the outcome of your query operations and it is quite efficient for long-running stream... - Source: dev.to / about 1 year ago
You can ingest data from different data sources such as message brokers Kafka, Redpanda, Kinesis, Pulsar, or databases MySQL or PostgreSQL using their Change Data Capture (CDC) which is the process of identifying and capturing data changes. - Source: dev.to / about 1 year ago
Apache Flume is an open-source log management tool designed to efficiently collect, aggregate, and transport large volumes of log data from various sources to a centralized data store, such as HDFS or Hbase. It excels in handling large amounts of log data in real-time and is highly scalable, able to handle the load from multiple servers, network devices, and applications. - Source: dev.to / about 1 year ago
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
Fluentd - Fluentd is a cross platform open source data collection solution originally developed at Treasure Data.
Confluent - Confluent offers a real-time data platform built around Apache Kafka.
Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
PieSync - Seamless two-way sync between your CRM, marketing apps and Google in no time
