Amazon Kinesis
Apache Flink
Confluent
Apache Kafka
PieSync
Azure Stream Analytics
Google Cloud Dataflow
Spark Streaming
Apache Druid
Apache Spark
Apache Hive
Apache Flink
Apache Kylin
ClickHouse
Amazon Athena
Presto DB
Amazon Kinesis Apache DruidBased on our record, Amazon Kinesis should be more popular than Apache Druid. It has been mentiond 22 times since March 2021. 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 / almost 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 Druid: Focused on real-time analytics and interactive queries on large datasets. Druid is well-suited for high-performance applications in user-facing analytics, network monitoring, and business intelligence. - Source: dev.to / about 2 months ago
Online analytical processing (OLAP) databases like Apache Druid, Apache Pinot, and ClickHouse shine in addressing user-initiated analytical queries. You might write a query to analyze historical data to find the most-clicked products over the past month efficiently using OLAP databases. When contrasting with streaming databases, they may not be optimized for incremental computation, leading to challenges in... - Source: dev.to / 3 months ago
Spencer Kimball (now CEO at CockroachDB) wrote an interesting article on this topic in 2021 where they created spencerkimball/stargazers based on a Python script. So I started thinking: could I create a data pipeline using Nifi and Kafka (two OSS tools often used with Druid) to get the API data into Druid - and then use SQL to do the analytics? The answer was yes! And I have documented the outcome below. Here’s... - Source: dev.to / over 1 year ago
Apache Druid is part of the modern data architecture. It uses a special data format designed for analytical workloads, using extreme parallelisation to get data in and get data out. A shared-nothing, microservices architecture helps you to build highly-available, extreme scale analytics features into your applications. - Source: dev.to / over 1 year ago
Datadog's product is a bit too close to Apache Druid to have named their design system so similarly. From https://druid.apache.org/ : > Druid unlocks new types of queries and workflows for clickstream, APM, supply chain, network telemetry, digital marketing, risk/fraud, and many other types of data. Druid is purpose built for rapid, ad-hoc queries on both real-time and historical data. - Source: Hacker News / over 1 year ago
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Confluent - Confluent offers a real-time data platform built around Apache Kafka.
Apache Hive - Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.
Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.
PieSync - Seamless two-way sync between your CRM, marketing apps and Google in no time
