Amazon Redshift Spectrum vs AresDB | What are the differences? | StackShare

Amazon Redshift Spectrum vs AresDB

Overview

Amazon Redshift Spectrum

Stacks99

Followers147

Votes3

AresDB

Stacks15

Followers47

Votes0

GitHub Stars3.1K

Forks235

Amazon Redshift Spectrum vs AresDB: What are the differences?

What is Amazon Redshift Spectrum? Exabyte-Scale In-Place Queries of S3 Data. With Redshift Spectrum, you can extend the analytic power of Amazon Redshift beyond data stored on local disks in your data warehouse to query vast amounts of unstructured data in your Amazon S3 “data lake” -- without having to load or transform any data.

What is AresDB? A GPU-powered real-time analytics storage and query engine (by Uber). AresDB is a GPU-powered real-time analytics storage and query engine. It features low query latency, high data freshness and highly efficient in-memory and on disk storage management.

Amazon Redshift Spectrum and AresDB belong to "Big Data Tools" category of the tech stack.

AresDB is an open source tool with 1.98K GitHub stars and 126 GitHub forks. Here's a link to AresDB's open source repository on GitHub.

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Detailed Comparison

Amazon Redshift Spectrum	AresDB
With Redshift Spectrum, you can extend the analytic power of Amazon Redshift beyond data stored on local disks in your data warehouse to query vast amounts of unstructured data in your Amazon S3 “data lake” -- without having to load or transform any data.	AresDB is a GPU-powered real-time analytics storage and query engine. It features low query latency, high data freshness and highly efficient in-memory and on disk storage management.
Statistics
GitHub Stars -	GitHub Stars 3.1K
GitHub Forks -	GitHub Forks 235
Stacks 99	Stacks 15
Followers 147	Followers 47
Votes 3	Votes 0
Pros & Cons
Pros 1 Economical 1 Great Documentation 1 Good Performance	No community feedback yet
Integrations
Amazon S3 Amazon Redshift	No integrations available

What are some alternatives to Amazon Redshift Spectrum, AresDB?

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.