
Apache Storm
Apache Spark
Apache Flink
Qubole
Hadoop
Google BigQuery
Apache Kafka
Amazon Kinesis
Apache Avro
Apache Ambari
Apache HBase
Apache Pig
Apache Mahout
Apache Oozie
gRPC
Apache Parquet
Apache Storm
Apache AvroApache Avro might be a bit more popular than Apache Storm. We know about 15 links to it since March 2021 and only 11 links to Apache Storm. 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.
There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 3 years ago
Although this article lists a lot of targets for technical selection, there are definitely others that I haven't listed, which may be either outdated, less-used options such as Apache Storm or out of my radar from the beginning, like JAVA ecosystem. - Source: dev.to / over 3 years ago
Storm, a system for real-time and stream processing. - Source: dev.to / over 3 years ago
Google has scaled well and has helped others scale, Twitter has always been behind by years. I think the only thing they did well was Twitter Storm, now taken up by Apache Foundation. Source: over 3 years ago
Streaming: Sparks Streamings's latency is at least 500ms, since it operates on micro-batches of records, instead of processing one record at a time. Native streaming tools like Storm, Apex or Flink might be better for low-latency applications. - Source: dev.to / over 4 years ago
Iceberg is able to efficiently manage large amounts of data stored in the data lake. The data layer supports storing data in open formats like Apache parquet or Avro. Apache Parquet is an open columnar data format for efficient data storage and retrieval. With this, you automatically get the benefits of column storage for your analytical workloads. Engines like Apache Spark, Apache Flink, Presto, Trino etc can be... - Source: dev.to / 9 months ago
A schema.json converter for easier ingestion (likely supporting Avro and Protobuf). - Source: dev.to / over 1 year ago
Security Aware Data Metadata Data schema formats such as Avro and Json currently lack built-in support for data sensitivity or security-aware metadata. Additionally, common formats like Parquet and Iceberg, while efficient for storing large datasets, donโt natively include security-aware metadata. At Jarrid, we are exploring various metadata formats to incorporate data sensitivity and security-aware attributes... - Source: dev.to / almost 2 years ago
Apache AVRO [1] is one but it has been largely replaced by Parquet [2] which is a hybrid row/columnar format [1] https://avro.apache.org/. - Source: Hacker News / over 2 years ago
The most common format for describing schema in this scenario is Apache Avro. - Source: dev.to / over 2 years ago
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Apache Ambari - Ambari is aimed at making Hadoop management simpler by developing software for provisioning, managing, and monitoring Hadoop clusters.
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
Apache HBase - Apache HBase โ Apache HBaseโข Home
Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.
Apache Pig - Pig is a high-level platform for creating MapReduce programs used with Hadoop.