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Apache Flink
Apache Flink

141
149
+ 1
11
Pilosa
Pilosa

0
5
+ 1
0
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Apache Flink vs Pilosa: What are the differences?

Apache Flink: Fast and reliable large-scale data processing engine. Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala; Pilosa: Open source, distributed bitmap index in Go. Pilosa is an open source, distributed bitmap index that dramatically accelerates queries across multiple, massive data sets.

Apache Flink and Pilosa belong to "Big Data Tools" category of the tech stack.

Apache Flink and Pilosa are both open source tools. Apache Flink with 9.35K GitHub stars and 5K forks on GitHub appears to be more popular than Pilosa with 1.83K GitHub stars and 149 GitHub forks.

What is Apache Flink?

Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.

What is Pilosa?

Pilosa is an open source, distributed bitmap index that dramatically accelerates queries across multiple, massive data sets.
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          What are some alternatives to Apache Flink and Pilosa?
          Apache Spark
          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 Storm
          Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate.
          Beam
          A distributed knowledge graph store. Knowledge graphs are suitable for modeling data that is highly interconnected by many types of relationships, like encyclopedic information about the world.
          Apache Flume
          It is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. It has a simple and flexible architecture based on streaming data flows. It is robust and fault tolerant with tunable reliability mechanisms and many failover and recovery mechanisms. It uses a simple extensible data model that allows for online analytic application.
          Kafka
          Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
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          How developers use Apache Flink and Pilosa
          Avatar of Coolfront Technologies
          Coolfront Technologies uses Apache FlinkApache Flink

          Used for analytics on streaming data.

          Avatar of rmetzger
          rmetzger uses Apache FlinkApache Flink

          Flink for stream data analytics

          How much does Apache Flink cost?
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