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Learn MorePros of Apache Spark
Pros of Steampipe
Pros of Apache Spark
- Open-source61
- Fast and Flexible48
- One platform for every big data problem8
- Great for distributed SQL like applications8
- Easy to install and to use6
- Works well for most Datascience usecases3
- Interactive Query2
- Machine learning libratimery, Streaming in real2
- In memory Computation2
Pros of Steampipe
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Cons of Apache Spark
Cons of Steampipe
Cons of Apache Spark
- Speed4
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What is 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.
What is Steampipe?
The open-source SQL interface to your favorite cloud APIs.
Select * from AWS, Azure, GCP, Github, Slack, and more.
It exposes APIs and services as a high-performance relational database, giving you the ability to write SQL-based queries and controls to explore, assess and report on dynamic data.
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What companies use Apache Spark?
What companies use Steampipe?
What companies use Apache Spark?
What companies use Steampipe?
See which teams inside your own company are using Apache Spark or Steampipe.
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What tools integrate with Apache Spark?
What tools integrate with Steampipe?
What tools integrate with Apache Spark?
What tools integrate with Steampipe?
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What are some alternatives to Apache Spark and Steampipe?
Hadoop
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
Splunk
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
Cassandra
Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
Apache Beam
It implements batch and streaming data processing jobs that run on any execution engine. It executes pipelines on multiple execution environments.
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.