Software Alternatives, Accelerators & Startups

Sensor Tower VS Apache Hive

Compare Sensor Tower VS Apache Hive and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Sensor Tower logo Sensor Tower

Sensor Tower is a platform for app store optimization and app industry intelligence.

Apache Hive logo Apache Hive

Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.
  • Sensor Tower Landing page
    Landing page //
    2023-06-21
  • Apache Hive Landing page
    Landing page //
    2023-01-13

Sensor Tower

$ Details
-
Release Date
2013 January
Startup details
Country
United States
State
California
Founder(s)
Alex Malafeev
Employees
100 - 249

Apache Hive

Pricing URL
-
$ Details
Release Date
-

Sensor Tower features and specs

  • Comprehensive App Data
    Sensor Tower offers detailed analytics and insights on app performance, including downloads, revenue, and user engagement. This data helps developers make informed decisions about their app strategies.
  • Market Intelligence
    The platform provides market intelligence that can help businesses understand market trends, competitive landscapes, and growth opportunities, enabling better strategic planning.
  • Advertising Analytics
    Sensor Tower includes features to track app advertising performance, providing insights into ad spend, impressions, and the effectiveness of ad campaigns.
  • Easy-to-Use Interface
    The platform's user-friendly interface makes it accessible for users with varying levels of technical expertise, which can be a significant advantage for small teams or individual developers.
  • ASO Tools
    Sensor Tower offers App Store Optimization (ASO) tools to help apps rank better in app store search results, enhancing visibility and potentially increasing downloads.

Possible disadvantages of Sensor Tower

  • Cost
    Sensor Tower is a premium service with a pricing model that may be prohibitive for small businesses or individual developers, especially those who are just starting out.
  • Learning Curve
    Although the interface is user-friendly, the extensive range of features and data can be overwhelming at first, requiring a learning curve to fully leverage the platform’s capabilities.
  • Data Limitations
    While Sensor Tower provides robust analytics, some users have noted occasional discrepancies or gaps in the data, which may impact the reliability of insights.
  • Competitor Focus
    The platform's focus on competitive intelligence can lead to an overemphasis on competitors' strategies rather than fostering innovation within one's own product.
  • Dependence on Data Accuracy
    Because decision-making relies heavily on the platform's data, any inaccuracies or outdated information can lead to misguided strategies and potential negative impacts on business outcomes.

Apache Hive features and specs

  • Scalability
    Apache Hive is built on top of Hadoop, allowing it to efficiently handle large datasets by distributing the load across a cluster of machines.
  • SQL-like Interface
    Hive provides a familiar SQL-like querying language, HiveQL, which makes it easier for users with SQL knowledge to perform data analysis on large datasets without needing to learn a new syntax.
  • Integration with Hadoop Ecosystem
    Hive integrates seamlessly with other components of the Hadoop ecosystem such as HDFS for storage and MapReduce for processing, making it a versatile tool for big data processing.
  • Schema on Read
    Hive uses a schema-on-read model which allows it to work with flexible data schemas and handle unstructured or semi-structured data efficiently.
  • Extensibility
    Users can extend Hive's capabilities by writing custom UDFs (User Defined Functions), UDAFs (User Defined Aggregate Functions), and SerDes (Serializers/ Deserializers).

Possible disadvantages of Apache Hive

  • Latency in Query Processing
    Queries in Hive often take longer to execute compared to traditional databases, as they are converted to MapReduce jobs which can introduce significant latency.
  • Limited Real-time Processing
    Hive is designed for batch processing and is not suitable for real-time analytics due to its reliance on MapReduce, which is not optimized for low-latency operations.
  • Complex Configuration
    Setting up Hive and configuring it to work optimally within a Hadoop cluster can be complex and require a significant amount of effort and expertise.
  • Lack of Support for Transactions
    Hive does not natively support full ACID transactions, which can be a limitation for applications that require consistent transaction management across large datasets.
  • Dependency on Hadoop
    Hive's reliance on the Hadoop ecosystem means it inherits some of Hadoop's limitations, such as a steep learning curve and the need for substantial resources to manage a cluster.

Sensor Tower videos

Sensor Tower ASO Tool Review: Keyword Spy, Research & Apple Features

More videos:

  • Review - ASO 101 and Sensor Tower Platform Overview
  • Review - Sensor Tower - App Store Optimization for iOS and Android

Apache Hive videos

Hive vs Impala - Comparing Apache Hive vs Apache Impala

Category Popularity

0-100% (relative to Sensor Tower and Apache Hive)
Analytics
100 100%
0% 0
Databases
0 0%
100% 100
App Store Optimization (ASO)
Big Data
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Sensor Tower should be more popular than Apache Hive. It has been mentiond 30 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Sensor Tower mentions (30)

  • 7 AI trends in mobile app development
    The hype around AI shows no signs of slowing down and continues to attract attention from publishers, developers, anyone creating mobile applications for their business, and those with a keen interest. This fact is proved by the latest report, State of AI, which analyzed current trends in 2025, released by Sensor Tower, the leading source of mobile app insights. If you haven’t had time to look through the report,... - Source: dev.to / 12 months ago
  • The Karma Connection in Chrome Web Store
    I was optimistically hoping some of the MV3 changes would result in Chrome webstore policy enforcement being standardized, but that hasn't happened. Sensor Tower (https://sensortower.com/) makes a lot of popular extensions, like StayFocusd https://www.stayfocusd.com/. They seem to resell ad data (in violation of [1]?) and ship likely obfuscated code [2] (in violation of [3]?), but there's no enforcement or even... - Source: Hacker News / almost 2 years ago
  • Famine Scourge Will Be Broken. Don’t Lose Focus.
    Yes, and they will be right. Just look at its revenue (sensortower.com) through the many fiascos. Source: about 4 years ago
  • Genshin Impact Mobile Revenue and Downloads [Updated May 2022]
    (source: https://sensortower.com/). Source: over 4 years ago
  • Top Games by user group
    Ya I checked out data.ai and sensortower.com. Both give pretty good overview data. But I think you're right, premium may be required for any in depth user information. Source: over 4 years ago
View more

Apache Hive mentions (9)

  • 15 AWS EMR Cost Optimization Tips to Slash Your EMR Spending (2025)
    AWS EMR (Elastic MapReduce) is a fully managed big data platform. It manages the setup, configuration, and tuning of open source frameworks like Apache Hadoop, Apache Spark, Apache Hive, Presto, and more at scale on AWS infrastructure. EMR handles cluster scaling, resource allocation, and lifecycle management. This allows you to work with large datasets for various use cases, from ETL pipelines to ML workloads.... - Source: dev.to / 9 months ago
  • Apache Iceberg as storage for on-premise data store (cluster)
    Trino or Hive for SQL querying. Get Trino/Hive to talk to Nessie. Source: over 3 years ago
  • In One Minute : Hadoop
    Hive, A data warehouse infrastructure that provides data summarization and ad hoc querying. - Source: dev.to / almost 4 years ago
  • Apache Spark, Hive, and Spring Boot — Testing Guide
    In this article, I'm showing you how to create a Spring Boot app that loads data from Apache Hive via Apache Spark to the Aerospike Database. More than that, I'm giving you a recipe for writing integration tests for such scenarios that can be run either locally or during the CI pipeline execution. The code examples are taken from this repository. - Source: dev.to / over 4 years ago
  • Jinja2 not formatting my text correctly. Any advice?
    ListItem(name='Apache Hive', website='https://hive.apache.org/', category='Interactive Query', short_description='Apache Hive is a data warehouse software project built on top of Apache Hadoop for providing data query and analysis. Hive gives an SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop.'),. Source: over 4 years ago
View more

What are some alternatives?

When comparing Sensor Tower and Apache Hive, you can also consider the following products

appfigures - Cross-platform app store analytics for all of your mobile apps.

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

App Annie - App Annie is a marketing analytics tool available for apps of all kinds. With App Annie, you can track sales, traffic, and a variety of other factors pertinent to monitoring an app's trajectory.

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

Mobile Action - Mobile Data Intelligence & Actionable Insights.

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.