Amundsen vs Apache Pinot

Overview

Amundsen

Stacks17

Followers42

Votes0

Apache Pinot

Stacks5

Followers3

Votes0

GitHub Stars5.9K

Forks1.4K

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Detailed Comparison

Amundsen	Apache Pinot
It is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting with data.	Apache Pinot is a fast, scalable real-time analytics database. It is a column-oriented distributed Online Analytics Processing (OLAP) database designed for high concurrency and low latency. It can scan petabyte-scale data and produce results even as fast as single-digit milliseconds.
Datasets (Tables) schema and usage frequency/popularity; Users bookmark, owner, frequent user; Dashboard popularity, lineage to datasets	Real-time ingestion (Kafka, Kinesis, Pulsar); Real-time upserts; Batch ingestion (Flink, Hadoop, Spark); SQL ingestion (Snowflake, BigQuery); Ingestion time pre-processing (transforms, flattening, rollups); Flexible indexing types (star-tree, Bloom filter, forward, inverted, geospatial, JSON, range, text, timestamp); Automatic data replication and partitioning; Encryption (on disk; transport); Easy table management (backfills, dynamic re-indexing, minions for dynamic data layout changes); Schema evolution; Nested columns
Statistics
GitHub Stars -	GitHub Stars 5.9K
GitHub Forks -	GitHub Forks 1.4K
Stacks 17	Stacks 5
Followers 42	Followers 3
Votes 0	Votes 0
Integrations
Google BigQuery Snowflake AWS Glue Superset Apache Hive	Google BigQuery Hadoop Kafka Apache Spark Amazon Kinesis Snowflake Apache Flink Apache Pulsar

What are some alternatives to Amundsen, Apache Pinot?

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

Distributed SQL Query Engine for Big Data

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 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

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 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™ 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

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

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.