Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.
It is a managed Spark and Hadoop service that lets you take advantage of open source data tools for batch processing, querying, streaming, and machine learning. It helps you create clusters quickly, manage them easily, and save money by turning clusters off when you don't need them. | It brings all your DevOps data into one practical, personalized, extensible view. Ingest, analyze, and visualize data from an ever-growing list of developer tools, with our free and open source product. It is most exciting for leaders and managers looking to make better sense of their development data, though it's useful for any developer looking to bring a more data-driven approach to their own practices. With DevLake you can ask your process any question, just connect and query. |
Spin up an autoscaling cluster in 90 seconds on custom machines;
Build fully managed Apache Spark, Apache Hadoop, Presto, and other OSS clusters;
Only pay for the resources you use and lower the total cost of ownership of OSS;
Encryption and unified security built into every cluster;
Accelerate data science with purpose-built clusters | Comprehensive understanding of software development lifecycle, digging workflow bottlenecks;
Timely review of team iteration performance, rapid feedback, agile adjustment;
Quickly build scenario-based data dashboards and drill down to analyze the root cause of problems;
Support custom SQL analysis and drag and drop to build scenario-based data views
|
Statistics | |
GitHub Stars - | GitHub Stars 131 |
GitHub Forks - | GitHub Forks 18 |
Stacks 33 | Stacks 4 |
Followers 28 | Followers 3 |
Votes 0 | Votes 0 |
Integrations | |

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.

Distributed SQL Query Engine for Big Data

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.

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 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™ 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.

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

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.

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