What is Kylo?
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.
Kylo is a tool in the Big Data Tools category of a tech stack.
Kylo is an open source tool with 782 GitHub stars and 374 GitHub forks. Here’s a link to Kylo's open source repository on GitHub
Why developers like Kylo?
Here’s a list of reasons why companies and developers use Kylo
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- 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
Kylo Alternatives & Comparisons
What are some alternatives to Kylo?
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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 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 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.
Hive facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage.
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.