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  1. Stackups
  2. Application & Data
  3. Databases
  4. Big Data Tools
  5. Druid vs Kylo

Druid vs Kylo

OverviewComparisonAlternatives

Overview

Druid
Druid
Stacks376
Followers867
Votes32
Kylo
Kylo
Stacks15
Followers40
Votes0
GitHub Stars1.1K
Forks571

Druid vs Kylo: What are the differences?

Druid: Fast column-oriented distributed data store. 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; Kylo: 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.

Druid and Kylo can be primarily classified as "Big Data" tools.

Druid and Kylo are both open source tools. Druid with 8.85K GitHub stars and 2.27K forks on GitHub appears to be more popular than Kylo with 744 GitHub stars and 358 GitHub forks.

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Detailed Comparison

Druid
Druid
Kylo
Kylo

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.

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
-
GitHub Stars
1.1K
GitHub Forks
-
GitHub Forks
571
Stacks
376
Stacks
15
Followers
867
Followers
40
Votes
32
Votes
0
Pros & Cons
Pros
  • 15
    Real Time Aggregations
  • 6
    Batch and Real-Time Ingestion
  • 5
    OLAP
  • 3
    OLAP + OLTP
  • 2
    Combining stream and historical analytics
Cons
  • 3
    Limited sql support
  • 2
    Joins are not supported well
  • 1
    Complexity
No community feedback yet
Integrations
Zookeeper
Zookeeper
ActiveMQ
ActiveMQ
Apache Spark
Apache Spark
Hadoop
Hadoop
Apache NiFi
Apache NiFi

What are some alternatives to Druid, 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.

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.

Azure Synapse

Azure Synapse

It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. It brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

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