Apache Flume Alternatives and Competitors
In this article, we will see the top alternatives of Apache Flume. The article enlists various tools that are alternatives to Apache Flume. Some of the top alternatives of Apache Flume are Apache Spark, Logstash, Apache Storm, Kafka, Apache Flink, Apache NiFi, Papertrail, and some more.
Let us now explore each one in detail.
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Top 10 Apache Flume Alternatives
1. Apache Spark
Apache Spark is an open-source data analytics tool. It is a unified analytical engine for processing large scale data. It is the best tool for batch processing as well as real-time stream processing, interactive queries, and machine learning. Apache Spark runs on any of Hadoop YARN, EC2, Apache Mesos, etc. It performs faster processing than Apache Hadoop. Apache Spark is perfect for distributed SQL like applications. It provides a single platform for all the big data-related problems. It is best for its in-memory computation. Apache Spark can process data in Hadoop HDFS, Hive, HBase, Cassandra, and any Hadoop InputFormat.
Logstash is an open-source tool. It dynamically transforms and prepares our data regardless of data format and complexity. It dynamically ingests, transforms, and ships our data without worrying about data format or complexity. Logstash can derive structure from the unstructured data with grok. It can derive decipher geo coordinates from the IP addresses. Logstash excludes or anonymizes sensitive fields, and thus provides ease for overall processing. Logstash filters parse each event as the data travels from the source to the store. It identifies the named fields for building structure and transforms them to bring on a common format. This ensures a more powerful analysis and helps in generating business value. It is a tool for managing logs and events. We can use it for collecting logs, parsing them, and storing them for later use.
3. Apache Storm
Apache Storm is an open-source real-time computation system. It is a distributed computing system. With Apache Storm, we can easily process unbounded streams of data, that is, data that have to start but no end. It is a simple tool that we can use with any programming language. It is amongst the top tools for real-time analytics, ETL, continuous computation, online machine learning, and many more. Apache Storm is a fast, fault-tolerant, and scalable tool. It guarantees data processing. Apache Storm can be integrated with the database technologies already in use.
4. Apache Kafka
Apache Kafka is a distributed publish-subscribe based messaging system. It is an open-source distributed streaming platform and a robust queue that is capable of handling high volumes of data. It enables users to pass messages from one end-point to another. Apache Kafka suits for offline as well as online message consumption. It is useful building real-time streaming data pipelines and real-time streaming applications. The real-time streaming pipelines get data between applications or systems. The real-time streaming applications transform or react to the data streams. Apache Kafka can be integrated with Apache Storm and Apache Spark for real-time streaming data analysis.
5. Apache Flink
Apache Flink is an open-source streaming platform. It gains its popularity because of its accuracy in data ingestion, and its feature of recoverability from failures. It is a highly scalable, fast, and reliable large scale data processing engine. Apache Flink supports both batches as well as real-time stream analytics in one system. It processes events at very high speed with low latency. Apache Flink can be used for batch processing, interactive processing, real-time stream processing, graph processing, iterative processing, in-memory processing. It is an open-source framework for fast and versatile data analytics in clusters.
6. Apache NiFi
Apache NiFi is a powerful, reliable, and easy to use system used to process and distribute data. It supports scalable and powerful directed graphs of data routing, system mediation logic, and transformation. It was built with the purpose of automating the flow of data between the systems. Apache NiFi provides a web-based User Interface for the purpose of creating, monitoring, & controlling data flows. NiFi data flow process is highly configurable and modifiable which modifies data at runtime.
It is a hosted log management tool for servers, cloud services, and applications. Papertrail allows all app logs, Syslog, text log files to aggregate in one place. It helps in detecting, resolving, and avoiding infrastructure problems by using log messages. We can search for a log from huge volumes of logs within seconds using Papertrail. It is easy to use, implement & understand. Papertrail can get visibility across all the systems in minutes. It is a powerful log management tool. It easily works with existing services.
ELK is the acronym for Elasticsearch, Logstash, and Kibana. It is another powerful log management tool. It started with an Elasticsearch which is a search and analytics engine. Elasticsearch is famous for its search. Then it grew with Logstash and Kibana. Logstash is a server‑side data processing pipeline. Logstash ingests data simultaneously from multiple sources, transforms data, and then sends data to a “stash” like Elasticsearch. Kibana the powerful visualization tool enables users to visualize data via charts and graphs in Elasticsearch.
It is an open-source powerful log management platform used for collecting, indexing, and analyzing structured as well as unstructured data from varieties of sources. Graylog is based on Elasticsearch, MongoDB, and Scala. It has a main server that receives data from its clients which are installed on different servers. It has a web interface that visualizes the data and allows it to work with the logs aggregated by the main server. Graylog can be used as a stash for the logs of the web applications. It allows engineers to analyze system behavior on the basis of per code line when it is integrated properly with a web application. We can use powerful query language on Graylog for searching through the terabytes of log data in order to discover and analyze important information.
Splunk is a software platform useful for searching, analyzing, and visualizing machine-generated data that are gathered from the applications, websites, devices, sensors, etc. It is also a powerful log management tool. Splunk automatically pulls data from different sources and can accept data of any format like .csv, config files, json, etc. It collects data from multiple sources in real-time. It is the easiest tool to install. Splunk provides functionality such as searching, analyzing, reporting as well as visualizing machine-generated data. Splunk embraces a huge market in the IT infrastructure.
I hope after reading this article you understand the Apache Flume alternatives and competitors. We can use Apache Spark, Apka Kafka, ELK, Logstash, Apache Storm, Apache Flink, and some more as an alternative to Apache Flume. Graylog, Papertrail, Apache NiFi are also the topmost log management tools for collecting, indexing, and analyzing log data generated from web applications, websites, etc.