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Apache Impala
Apache Impala

58
55
+ 1
8
s3-lambda
s3-lambda

3
19
+ 1
0
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s3-lambda vs Apache Impala: What are the differences?

s3-lambda: Lambda functions over S3 objects: each, map, reduce, filter. s3-lambda enables you to run lambda functions over a context of S3 objects. It has a stateless architecture with concurrency control, allowing you to process a large number of files very quickly. This is useful for quickly prototyping complex data jobs without an infrastructure like Hadoop or Spark; Apache Impala: Real-time Query for Hadoop. Impala is a modern, open source, MPP SQL query engine for Apache Hadoop. Impala is shipped by Cloudera, MapR, and Amazon. With Impala, you can query data, whether stored in HDFS or Apache HBase – including SELECT, JOIN, and aggregate functions – in real time.

s3-lambda and Apache Impala belong to "Big Data Tools" category of the tech stack.

s3-lambda and Apache Impala are both open source tools. It seems that Apache Impala with 2.19K GitHub stars and 825 forks on GitHub has more adoption than s3-lambda with 1.05K GitHub stars and 41 GitHub forks.

What is Apache Impala?

Impala is a modern, open source, MPP SQL query engine for Apache Hadoop. Impala is shipped by Cloudera, MapR, and Amazon. With Impala, you can query data, whether stored in HDFS or Apache HBase – including SELECT, JOIN, and aggregate functions – in real time.

What is s3-lambda?

s3-lambda enables you to run lambda functions over a context of S3 objects. It has a stateless architecture with concurrency control, allowing you to process a large number of files very quickly. This is useful for quickly prototyping complex data jobs without an infrastructure like Hadoop or Spark.
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          What are some alternatives to Apache Impala and s3-lambda?
          Presto
          Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes.
          Apache Drill
          Apache Drill is a distributed MPP query layer that supports SQL and alternative query languages against NoSQL and Hadoop data storage systems. It was inspired in part by Google's Dremel.
          Apache Hive
          Hive facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage.
          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.
          Amazon Athena
          Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.
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