StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. Application & Data
  3. Databases
  4. Big Data Tools
  5. Kylo vs s3-lambda

Kylo vs s3-lambda

OverviewComparisonAlternatives

Overview

s3-lambda
s3-lambda
Stacks4
Followers64
Votes0
GitHub Stars1.1K
Forks47
Kylo
Kylo
Stacks15
Followers40
Votes0
GitHub Stars1.1K
Forks571

s3-lambda vs Kylo: What are the differences?

Developers describe s3-lambda as "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. On the other hand, Kylo is detailed as "Open-source data lake management software platform". It is an open source enterprise-ready data lake management software platform for self-service data ingest and data preparation with integrated metadata management, governance, security and best practices inspired by Think Big's 150+ big data implementation projects.

s3-lambda and Kylo can be categorized as "Big Data" tools.

s3-lambda and Kylo are both open source tools. s3-lambda with 1.06K GitHub stars and 42 forks on GitHub appears to be more popular than Kylo with 744 GitHub stars and 358 GitHub forks.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Detailed Comparison

s3-lambda
s3-lambda
Kylo
Kylo

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.

It is an open source enterprise-ready data lake management software platform for self-service data ingest and data preparation with integrated metadata management, governance, security and best practices inspired by Think Big's 150+ big data implementation projects.

-
Self-service data ingest with data cleansing, validation, and automatic profiling; Wrangle data with visual sql and an interactive transform through a simple user interface; Search and explore data and metadata, view lineage, and profile statistics; Monitor health of feeds and services in the data lake. Track SLAs and troubleshoot performance
Statistics
GitHub Stars
1.1K
GitHub Stars
1.1K
GitHub Forks
47
GitHub Forks
571
Stacks
4
Stacks
15
Followers
64
Followers
40
Votes
0
Votes
0
Integrations
Amazon S3
Amazon S3
AWS Lambda
AWS Lambda
ActiveMQ
ActiveMQ
Apache Spark
Apache Spark
Hadoop
Hadoop
Apache NiFi
Apache NiFi

What are some alternatives to s3-lambda, Kylo?

Apache Spark

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.

Presto

Presto

Distributed SQL Query Engine for Big Data

Amazon Athena

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.

Apache Flink

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.

lakeFS

lakeFS

It is an open-source data version control system for data lakes. It provides a “Git for data” platform enabling you to implement best practices from software engineering on your data lake, including branching and merging, CI/CD, and production-like dev/test environments.

Druid

Druid

Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.

Apache Kylin

Apache Kylin

Apache Kylin™ is an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop/Spark supporting extremely large datasets, originally contributed from eBay Inc.

Splunk

Splunk

It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.

Apache Impala

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.

Vertica

Vertica

It provides a best-in-class, unified analytics platform that will forever be independent from underlying infrastructure.

Related Comparisons

Bootstrap
Materialize

Bootstrap vs Materialize

Laravel
Django

Django vs Laravel vs Node.js

Bootstrap
Foundation

Bootstrap vs Foundation vs Material UI

Node.js
Spring Boot

Node.js vs Spring-Boot

Liquibase
Flyway

Flyway vs Liquibase