AtScale vs Fload
Overview
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CLI (Node.js)
Manual
Detailed Comparison
Its Virtual Data Warehouse delivers performance, security and agility to exceed the demands of modern-day operational analytics. | Fload is a powerful AI tool designed specifically for mobile app operators, providing them with enhanced data analysis capabilities. By transforming complex data into clear, actionable insights, Fload enables users to effectively monitor performance, identify trends, and make informed decisions more quickly. With its user-friendly interface and advanced analytics, Fload streamlines the decision-making process, helping businesses optimize their mobile applications for better results. Elevate your app strategy with Fload today |
Multiple SQL-on-Hadoop Engine Support;
Access Data Where it Lays;
Built-in Support for Complex Data Types;
Single Drop-in Gateway Node Deployment | Data analysis, Perfomance monitoring, Trend identification, Actionable insights, User friendly interface, Fast decision making, Optimization |
Statistics | |
Stacks 25 | Stacks 0 |
Followers 83 | Followers 1 |
Votes 0 | Votes 1 |
Integrations | |
| No integrations available | |
What are some alternatives to AtScale, Fload?
Mixpanel
Mixpanel helps companies build better products through data. With our powerful, self-serve product analytics solution, teams can easily analyze how and why people engage, convert, and retain to improve their user experience.
Metabase
It is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating.
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.
Superset
Superset's main goal is to make it easy to slice, dice and visualize data. It empowers users to perform analytics at the speed of thought.
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.
Amplitude
Amplitude provides scalable mobile analytics that helps companies leverage data to create explosive user growth. Anyone in the company can use Amplitude to pinpoint the most valuable behavioral patterns within hours.
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.
